1. X-rays are a form of electromagnetic radiation used in medical imaging to visualize bone structure and detect foreign objects.
2. During an X-ray exam, X-rays pass through the body, with different tissues absorbing varying amounts depending on their atomic makeup. Bones appear white on the resulting radiograph because they absorb most of the X-rays.
3. While X-rays provide valuable information, they also carry risks due to the ionizing radiation. Digital systems are replacing film-based ones to avoid unnecessary exposure.
The document discusses the fundamental steps in digital image processing. It describes 7 key steps: (1) image acquisition, (2) image enhancement, (3) image restoration, (4) color image processing, (5) wavelets and multiresolution processing, (6) image compression, and (7) morphological processing. For each step, it provides brief explanations of the techniques and purposes involved in digital image processing.
1. Digital image processing focuses on improving images for human interpretation and machine perception. It involves digitizing an image using sensors and processors then displaying the digital image.
2. The key stages of digital image processing are enhancement, restoration, compression, and registration. Registration involves mapping image frames for tasks like object recognition.
3. Common processing techniques include contrast intensification to improve poor contrast, smoothing to reduce noise, and sharpening to enhance blurred details.
Digital Image Processing and gis software systemsNirmal Kumar
The document provides an overview of digital image processing (DIP) and geographic information systems (GIS) software systems, outlining the key hardware and software components needed for DIP including processors, memory, displays, storage, operating systems, compilers, and image processing software. It also describes important image processing functions such as preprocessing, display and enhancement, information extraction, photogrammetric information extraction, and integration with GIS. Open source DIP and GIS software like ILWIS are also mentioned.
Introduction to Image Processing:Image ModalitiesKalyan Acharjya
This document provides an overview of digital image processing and various imaging modalities. It discusses how digital image processing is used across many fields today. It also summarizes different types of imaging modalities like gamma ray, X-ray, UV, visible light, IR, microwave, radio, acoustic and electron microscopy imaging. The document encourages readers to be aware of the wide applications of digital image processing.
Images are visual representations that can be used to record and present information. There are various techniques for acquiring, processing, and manipulating digital images with computers. The fundamental steps in digital image processing typically involve image acquisition, enhancement, restoration, compression, and segmentation. Imaging systems cover a wide range of the electromagnetic spectrum and light is commonly used for imaging due to its safe, reliable, and controllable properties.
The document discusses digital image processing and provides an overview of key concepts. It defines digital and analog images and explains how digital images are represented by pixels. It outlines fundamental steps in digital image processing like image acquisition, enhancement, restoration, morphological processing, segmentation, representation, compression and object recognition. It also discusses applications in areas like remote sensing, medical imaging, film and video effects.
Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.
The document discusses the fundamental steps in digital image processing. It describes 7 key steps: (1) image acquisition, (2) image enhancement, (3) image restoration, (4) color image processing, (5) wavelets and multiresolution processing, (6) image compression, and (7) morphological processing. For each step, it provides brief explanations of the techniques and purposes involved in digital image processing.
1. Digital image processing focuses on improving images for human interpretation and machine perception. It involves digitizing an image using sensors and processors then displaying the digital image.
2. The key stages of digital image processing are enhancement, restoration, compression, and registration. Registration involves mapping image frames for tasks like object recognition.
3. Common processing techniques include contrast intensification to improve poor contrast, smoothing to reduce noise, and sharpening to enhance blurred details.
Digital Image Processing and gis software systemsNirmal Kumar
The document provides an overview of digital image processing (DIP) and geographic information systems (GIS) software systems, outlining the key hardware and software components needed for DIP including processors, memory, displays, storage, operating systems, compilers, and image processing software. It also describes important image processing functions such as preprocessing, display and enhancement, information extraction, photogrammetric information extraction, and integration with GIS. Open source DIP and GIS software like ILWIS are also mentioned.
Introduction to Image Processing:Image ModalitiesKalyan Acharjya
This document provides an overview of digital image processing and various imaging modalities. It discusses how digital image processing is used across many fields today. It also summarizes different types of imaging modalities like gamma ray, X-ray, UV, visible light, IR, microwave, radio, acoustic and electron microscopy imaging. The document encourages readers to be aware of the wide applications of digital image processing.
Images are visual representations that can be used to record and present information. There are various techniques for acquiring, processing, and manipulating digital images with computers. The fundamental steps in digital image processing typically involve image acquisition, enhancement, restoration, compression, and segmentation. Imaging systems cover a wide range of the electromagnetic spectrum and light is commonly used for imaging due to its safe, reliable, and controllable properties.
The document discusses digital image processing and provides an overview of key concepts. It defines digital and analog images and explains how digital images are represented by pixels. It outlines fundamental steps in digital image processing like image acquisition, enhancement, restoration, morphological processing, segmentation, representation, compression and object recognition. It also discusses applications in areas like remote sensing, medical imaging, film and video effects.
Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.
Image processing involves manipulating digital images through algorithms implemented on computers. A digital image is composed of picture elements called pixels arranged in a grid. Each pixel represents a color or intensity value. Common image processing tasks include computer vision, optical character recognition, medical imaging, and more. Key concepts in image processing include pixels, resolution, color depth, and filtering/manipulating pixel values.
This document provides an overview of digital image processing. It discusses what digital images are composed of and how they are processed using computers. The key steps in digital image processing are described as image acquisition, enhancement, restoration, representation and description, and recognition. A variety of techniques can be used at each step like filtering, segmentation, morphological operations, and compression. The document also outlines common sources of digital images, such as from the electromagnetic spectrum, and applications like medical imaging, astronomy, security screening, and human-computer interfaces.
This document outlines an introductory course on basic image processing taught by Dr. Arne Seitz at the Swiss Institute of Technology (EPFL). It discusses key topics like file formats, image viewers, representation and processing programs. Specific techniques covered include lookup tables, brightness/contrast adjustment, filtering, thresholding, and measurements. ImageJ is demonstrated as a tool for visualizing and manipulating digital images. The goal is to provide foundational concepts for working with and analyzing digital microscope images.
This document discusses image processing and summarizes several key techniques. It begins by defining image processing and describing how images are digitized and processed. It then summarizes three main categories of image processing: image enhancement, image restoration, and image compression. Specific techniques discussed include contrast stretching, density slicing, and edge enhancement. The document also discusses visual saliency models, motion saliency, and using conditional random fields for video object extraction.
Image processing techniques can be used for face recognition applications. The process involves decomposing face images into subbands using discrete wavelet transform. The mid-frequency subband is selected and principal component analysis is applied to extract representational bases. These bases are stored for training images and used to translate probe images into representations which are classified to identify faces by matching with training representations. This approach segments discriminatory facial features to recognize identities despite variations in illumination, pose, expression and other factors.
The document discusses the fundamentals of digital image processing. It defines a digital image as a 2D function where amplitude at each point represents intensity or gray level. A digital image is composed of pixels which are discrete image elements. Image processing includes low-level tasks like noise reduction, mid-level tasks like segmentation, and high-level tasks like object recognition. Mathematical representation of a digital image involves illumination and reflectance components. Intensity at each point in a monochrome image represents its gray level value within the gray scale range from minimum to maximum.
Image processing is a technique that involves performing operations on digital images to enhance, analyze, or otherwise process them. It has applications in many fields including medical imaging, astronomy, biometrics, and more. Key stages in image processing include image acquisition, enhancement, restoration, segmentation, representation/description, compression, and object recognition. Image processing can be used for security purposes like steganography, as well as in fields like medical imaging, traffic management, robotics, and more. It transforms images into digital formats and allows for manipulation of image data.
This document provides an overview of image processing presented by four students. It discusses the introduction, need, types, techniques and applications of image processing. The key techniques described include geometric transformations, image smoothing, and contrast enhancement. Applications mentioned are in gaming, robotics, medical imaging, fingerprint recognition and more. The document outlines the current and future scope of image processing in areas like Google Image search, medical implants, drone monitoring and delivery.
Image processing involves improving visual appearance for human viewers and preparing images for measuring features and structures. It requires hardware with high resolution displays, sufficient storage and power, and memory bandwidth. Software like Photoshop and Corel Draw are used. Image processing of satellite data includes rectification and restoration, enhancement, and information extraction - the pre-processing of data, improving display for interpretation, and generating maps through classification.
Introduction to Digital Image ProcessingNagashree Bn
The document defines digital image processing and describes the key components of a digital image processing system. It discusses the major components which include image sensing, specialized hardware, computers, software modules to perform tasks like preprocessing, enhancement and compression. It also covers mass storage, image displays, hardcopy devices and networking capabilities required for a digital image processing system. Applications of digital image processing discussed include medical imaging, remote sensing, astronomy and more.
This document provides an overview of image processing. It defines image processing as any form of signal processing where the input is an image, such as photos or video frames, and the output can be another image or parameters related to the image. The document discusses applications of image processing like face detection and medical imaging. It also outlines different types of image processing, components used in image processing systems, and the future potential of image processing with more powerful computing. In conclusion, the document states that image processing techniques can enhance, analyze, and construct images for various applications.
Digital Image Processing_ ch1 introduction-2003Malik obeisat
The document provides an introduction to digital image processing. It defines a digital image as a finite set of digital values representing a two-dimensional image. Digital image processing focuses on improving images for human interpretation and processing images for machine perception. The document outlines the history of digital image processing and provides examples of its use in applications such as image enhancement, medical imaging, satellite imagery, and industrial inspection. It also describes common stages in digital image processing like image acquisition, enhancement, restoration, segmentation, and compression.
Introduction to digital image processing, image processing, digital image, analog image, formation of digital image, level of digital image processing, components of a digital image processing system, advantages of digital image processing, limitations of digital image processing, fields of digital image processing, ultrasound imaging, x-ray imaging, SEM, PET, TEM
Digital image processing involves performing operations on digital images using computer algorithms. It has several functional categories including image restoration to remove noise and distortions, enhancement to modify the visual impact, and information extraction to analyze images. The main steps are acquisition, enhancement, restoration, color processing, compression, segmentation, and filtering using techniques like pixelization, principal components analysis, and neural networks. It has applications in medical imaging, film, transmission, sensing, and robotics. The advantages are noise removal, flexibility in format and manipulation, and easy storage and retrieval. The disadvantages can include high initial costs and potential data loss if storage devices fail.
This document provides an overview of digital image processing. It defines what an image is, noting that an image is a spatial representation of a scene represented as an array of pixels. Digital image processing refers to processing digital images on a computer. The key steps in digital image processing are image acquisition, enhancement, restoration, compression, morphological processing, segmentation, representation, and recognition. Digital image processing has many applications including medical imaging, traffic monitoring, biometrics, and computer vision.
01 introduction image processing analysisRumah Belajar
This document provides an introduction to image processing and analysis. It discusses image acquisition, pre-processing techniques like image transforms and enhancement, and applications of image processing. Image transforms like the discrete Fourier transform and discrete cosine transform are used to represent images in different domains. Image enhancement techniques accentuate features to make images more useful for display and analysis. Common techniques include adjusting histograms, using median filters, and performing operations in transform domains.
From gamma ray imaging in space to medical diagnosticsGunnar Maehlum
Talk given at the transatlantic science week, innovation frontiers, University of California, Berkeley, October 2011.
The talk describes how space technology can be used in Medicine.
Biomedical Data: Their Acquisition, Storage & Use. - Security and PrivacyDr. Khaled OUANES
The document discusses key concepts for biomedical computing including the data-to-knowledge spectrum, data acquisition and storage, and security issues. It explains that data is raw facts, information is the analysis of data, and knowledge is gained from further analysis of information. Examples are given around blood pressure readings and diagnosing hypertension. The importance of concepts like organization, management, and technology for addressing challenges in biomedical computing are also outlined.
COMPLETE MEDICAL EQUIPMENTS- HBOT PRESENTATION -SECHRISTatulforcomplete
Man can survive without food for weeks, and without water for days, but only minutes without oxygen. Oxygen is the basis of life. This document discusses hyperbaric oxygen therapy (HBOT) which involves breathing high concentrations of oxygen in a pressurized chamber. HBOT increases the amount of oxygen that dissolves in the patient's plasma which can help various conditions such as wounds, radiation injuries, and gas or carbon monoxide poisoning.
Image processing involves manipulating digital images through algorithms implemented on computers. A digital image is composed of picture elements called pixels arranged in a grid. Each pixel represents a color or intensity value. Common image processing tasks include computer vision, optical character recognition, medical imaging, and more. Key concepts in image processing include pixels, resolution, color depth, and filtering/manipulating pixel values.
This document provides an overview of digital image processing. It discusses what digital images are composed of and how they are processed using computers. The key steps in digital image processing are described as image acquisition, enhancement, restoration, representation and description, and recognition. A variety of techniques can be used at each step like filtering, segmentation, morphological operations, and compression. The document also outlines common sources of digital images, such as from the electromagnetic spectrum, and applications like medical imaging, astronomy, security screening, and human-computer interfaces.
This document outlines an introductory course on basic image processing taught by Dr. Arne Seitz at the Swiss Institute of Technology (EPFL). It discusses key topics like file formats, image viewers, representation and processing programs. Specific techniques covered include lookup tables, brightness/contrast adjustment, filtering, thresholding, and measurements. ImageJ is demonstrated as a tool for visualizing and manipulating digital images. The goal is to provide foundational concepts for working with and analyzing digital microscope images.
This document discusses image processing and summarizes several key techniques. It begins by defining image processing and describing how images are digitized and processed. It then summarizes three main categories of image processing: image enhancement, image restoration, and image compression. Specific techniques discussed include contrast stretching, density slicing, and edge enhancement. The document also discusses visual saliency models, motion saliency, and using conditional random fields for video object extraction.
Image processing techniques can be used for face recognition applications. The process involves decomposing face images into subbands using discrete wavelet transform. The mid-frequency subband is selected and principal component analysis is applied to extract representational bases. These bases are stored for training images and used to translate probe images into representations which are classified to identify faces by matching with training representations. This approach segments discriminatory facial features to recognize identities despite variations in illumination, pose, expression and other factors.
The document discusses the fundamentals of digital image processing. It defines a digital image as a 2D function where amplitude at each point represents intensity or gray level. A digital image is composed of pixels which are discrete image elements. Image processing includes low-level tasks like noise reduction, mid-level tasks like segmentation, and high-level tasks like object recognition. Mathematical representation of a digital image involves illumination and reflectance components. Intensity at each point in a monochrome image represents its gray level value within the gray scale range from minimum to maximum.
Image processing is a technique that involves performing operations on digital images to enhance, analyze, or otherwise process them. It has applications in many fields including medical imaging, astronomy, biometrics, and more. Key stages in image processing include image acquisition, enhancement, restoration, segmentation, representation/description, compression, and object recognition. Image processing can be used for security purposes like steganography, as well as in fields like medical imaging, traffic management, robotics, and more. It transforms images into digital formats and allows for manipulation of image data.
This document provides an overview of image processing presented by four students. It discusses the introduction, need, types, techniques and applications of image processing. The key techniques described include geometric transformations, image smoothing, and contrast enhancement. Applications mentioned are in gaming, robotics, medical imaging, fingerprint recognition and more. The document outlines the current and future scope of image processing in areas like Google Image search, medical implants, drone monitoring and delivery.
Image processing involves improving visual appearance for human viewers and preparing images for measuring features and structures. It requires hardware with high resolution displays, sufficient storage and power, and memory bandwidth. Software like Photoshop and Corel Draw are used. Image processing of satellite data includes rectification and restoration, enhancement, and information extraction - the pre-processing of data, improving display for interpretation, and generating maps through classification.
Introduction to Digital Image ProcessingNagashree Bn
The document defines digital image processing and describes the key components of a digital image processing system. It discusses the major components which include image sensing, specialized hardware, computers, software modules to perform tasks like preprocessing, enhancement and compression. It also covers mass storage, image displays, hardcopy devices and networking capabilities required for a digital image processing system. Applications of digital image processing discussed include medical imaging, remote sensing, astronomy and more.
This document provides an overview of image processing. It defines image processing as any form of signal processing where the input is an image, such as photos or video frames, and the output can be another image or parameters related to the image. The document discusses applications of image processing like face detection and medical imaging. It also outlines different types of image processing, components used in image processing systems, and the future potential of image processing with more powerful computing. In conclusion, the document states that image processing techniques can enhance, analyze, and construct images for various applications.
Digital Image Processing_ ch1 introduction-2003Malik obeisat
The document provides an introduction to digital image processing. It defines a digital image as a finite set of digital values representing a two-dimensional image. Digital image processing focuses on improving images for human interpretation and processing images for machine perception. The document outlines the history of digital image processing and provides examples of its use in applications such as image enhancement, medical imaging, satellite imagery, and industrial inspection. It also describes common stages in digital image processing like image acquisition, enhancement, restoration, segmentation, and compression.
Introduction to digital image processing, image processing, digital image, analog image, formation of digital image, level of digital image processing, components of a digital image processing system, advantages of digital image processing, limitations of digital image processing, fields of digital image processing, ultrasound imaging, x-ray imaging, SEM, PET, TEM
Digital image processing involves performing operations on digital images using computer algorithms. It has several functional categories including image restoration to remove noise and distortions, enhancement to modify the visual impact, and information extraction to analyze images. The main steps are acquisition, enhancement, restoration, color processing, compression, segmentation, and filtering using techniques like pixelization, principal components analysis, and neural networks. It has applications in medical imaging, film, transmission, sensing, and robotics. The advantages are noise removal, flexibility in format and manipulation, and easy storage and retrieval. The disadvantages can include high initial costs and potential data loss if storage devices fail.
This document provides an overview of digital image processing. It defines what an image is, noting that an image is a spatial representation of a scene represented as an array of pixels. Digital image processing refers to processing digital images on a computer. The key steps in digital image processing are image acquisition, enhancement, restoration, compression, morphological processing, segmentation, representation, and recognition. Digital image processing has many applications including medical imaging, traffic monitoring, biometrics, and computer vision.
01 introduction image processing analysisRumah Belajar
This document provides an introduction to image processing and analysis. It discusses image acquisition, pre-processing techniques like image transforms and enhancement, and applications of image processing. Image transforms like the discrete Fourier transform and discrete cosine transform are used to represent images in different domains. Image enhancement techniques accentuate features to make images more useful for display and analysis. Common techniques include adjusting histograms, using median filters, and performing operations in transform domains.
From gamma ray imaging in space to medical diagnosticsGunnar Maehlum
Talk given at the transatlantic science week, innovation frontiers, University of California, Berkeley, October 2011.
The talk describes how space technology can be used in Medicine.
Biomedical Data: Their Acquisition, Storage & Use. - Security and PrivacyDr. Khaled OUANES
The document discusses key concepts for biomedical computing including the data-to-knowledge spectrum, data acquisition and storage, and security issues. It explains that data is raw facts, information is the analysis of data, and knowledge is gained from further analysis of information. Examples are given around blood pressure readings and diagnosing hypertension. The importance of concepts like organization, management, and technology for addressing challenges in biomedical computing are also outlined.
COMPLETE MEDICAL EQUIPMENTS- HBOT PRESENTATION -SECHRISTatulforcomplete
Man can survive without food for weeks, and without water for days, but only minutes without oxygen. Oxygen is the basis of life. This document discusses hyperbaric oxygen therapy (HBOT) which involves breathing high concentrations of oxygen in a pressurized chamber. HBOT increases the amount of oxygen that dissolves in the patient's plasma which can help various conditions such as wounds, radiation injuries, and gas or carbon monoxide poisoning.
Towards Biomedical Research as a Digital EnterprisePhilip Bourne
Philip Bourne outlines his vision of transforming biomedical research into a digital enterprise by making data and other digital assets more open, interoperable, and accessible across boundaries through initiatives like the NIH's Big Data to Knowledge initiative; this would help address issues like the slow pace of discovery and non-reproducibility of research by better connecting scientists and their work.
The document outlines the fundamental aspects of managing a service department, including:
1) The mission is to provide customers with the best end-to-end service through customer-oriented and fast reaction implementation.
2) Key assets include managing resources like manpower, tools, equipment, spare parts, budgets, and timelines to maximize support with minimum costs.
3) The vision is to promote company services, solutions, and improve customer satisfaction.
To solve problems such as lacking accesses, shortage of useful information about small problems, and confusing about what happens. ONES provides multi-access (phone, mobile phone, website, SMS, and Email) to help customers schedule their service, gather and share the experience, and track the process. The aim of it is to enhance the efficiency and flexibility of customer experiences.
Measurement & calibration of medical equipmentsJumaan AlAmri
This document discusses the roles of biomedical equipment technicians (BMETs) and clinical engineers. It provides definitions for key terms in metrology and instrumentation. BMETs are responsible for preventative maintenance, repairs, and calibrations of medical devices, though some complex equipment require certification. Clinical engineers apply engineering skills to healthcare technology including managing equipment calibration/repair and ensuring regulatory compliance. Documentation protocols are also established to record equipment details, maintenance, and quality assurance processes. The conclusion emphasizes the need for BMETs to receive specialized training from manufacturers to safely service advanced medical technology.
This document outlines the curriculum for an orientation module on biomedical equipment repair and maintenance. The module aims to provide an understanding of the field of biomedical equipment technology and the role of biomedical equipment technicians. Key topics covered include the history and development of biomedical technology, the duties and responsibilities of technicians, and hospital and organizational structures. Assessment includes a semester exam and assignments based on field visits and group discussions.
Assessment of maintenance management systemSagar Sharma
This document provides an overview of Sagar Kumar Sharma's assessment report on the maintenance management system at BITS Pilani. It discusses key aspects of maintenance including definitions, objectives, procedures, policies, planning, scheduling, costs, and performance indicators. The report covers maintenance history, classifications of maintenance problems, cost control methods, and concepts like reliability centered maintenance and total productive maintenance.
Project Management and Innovation in Biomedical Engineering. Section 1: Conce...Aurelio Ruiz Garcia
Set of slides for Section 1 of the course "Project Management and Innovation in Biomedical Engineering". Biomedical Engineering - UPF (2013-14)
Introduction to management concepts, innovation management, business models, value chain, strategies, design of communication plans.
biomedical research in an increasingly digital worldBrian Bot
This document summarizes a presentation by Brian Bot from Sage Bionetworks on biomedical research in an increasingly digital world. It discusses how Sage Bionetworks is a non-profit organization that pilots various tools and components to build an open scientific research commons, including tools for collaborative science, re-imagined informed consent involving patients as partners, and the Patient-Centered Consent toolkit. It also provides examples of collaborations like the TCGA Pan-Cancer Consortium and CRC Subtyping Consortium that work on common data and questions, and partnerships like the Accelerating Medicines Partnership that harmonize incentives toward shared goals.
Biomedical Research as an Open Digital EnterprisePhilip Bourne
The document discusses the challenges and opportunities facing biomedical research as it transitions to becoming a fully digital open enterprise. It notes issues around reproducibility, limited funding, and the need to better connect different elements of the research lifecycle like data capture, analysis, and publication. The author proposes the "Commons" as a conceptual framework to help address these issues by providing shared resources like cloud-based storage and computing, tools to discover and access data and software, and standards to improve reproducibility. The goal is to foster an ecosystem that maximizes the benefits of digital technologies for biomedical research.
This lecture discusses the development of nuclear imaging techniques. It begins with an overview of nuclear imaging and its use of gamma rays and x-rays to form images. The earliest device was the rectilinear scanner, which used a single moving detector. The Anger gamma camera was a significant improvement as it allowed simultaneous detection over a large area. Modern gamma cameras use NaI(Tl) scintillator crystals coupled to PMTs to convert gamma ray interactions to light and then electrical signals. Digital processing is used to determine interaction locations and form images. Collimators are used to selectively detect gamma rays from a desired direction.
This document provides an overview of how to interpret chest x-rays. It discusses the basic principles of how x-rays pass through and are absorbed by different tissues. It also covers the standard views, techniques for obtaining adequate images, and how to identify common anatomical structures and pathologies like cardiomegaly, pleural effusions, pneumothorax, and various lung diseases. The goal is to understand how to evaluate chest x-rays and recognize normal anatomy and common abnormalities.
Developing short answer questions (sa qs)Javed Iqbal
The document provides guidance on developing short answer questions (SAQs) for assessments. It discusses the criteria for good SAQ items, including being objective, valid, reliable, and feasible. SAQs are intended to test interpretation, reasoning, and problem-solving skills rather than just knowledge. An example is provided demonstrating how to construct an SAQ item using a clinical vignette linked to 3-4 questions with restricted point-wise answers and assigned marks. The key considerations in developing SAQs are selecting appropriate wording, constructing the answer key, and assigning marks to answers.
Biological control systems - Time Response Analysis - S.Mathankumar-VMKVECMathankumar S
Biological control systems - Time Response Analysis - Step and Impulse responses of first order and second order systems, Determination of time domain specifications of first and second order systems from its output responses.
HOW TO PROVIDE EXCELLENT AFTER SALE SERVICE by
learning about customer service engagement strategies and about managing expectations.
RESOURCES----------
BLOGS
Zen Desk Blog [www.zendesk.com/blog]
Help Scout Blog [www.helpscout.net/blog]
BOOKS
Exceeding Customer Expectations by Kirk Kazanjian
Driving Loyalty by Kirk Kazanjian
Zingerman’s Guide to Service by Ari Weinzweig
Nice Companies Finish First by Peter Shankman
Satisfaction by Chris Denove
These slides were part of a presentation given at an
I Love Marketing Meetup
In Tempe, Arizona on August 16, 2013.
I Love Marketing is a Podcast by Joe Polish and Dean Jackson where they talk about new marketing ideas, direct mail ideas, lead generation, lead conversion, getting referrals, stick strategies, email marketing, psychology, books, people and even productivity.
Find out more at ilovemarketing.com or
Listen to the podcasts on iTunes
Contribution of biomedical engineers to healthcare developmentHani M. Bu-Omer
The document discusses biomedical engineering, including what it is, its branches, the roles of biomedical engineers, careers in the field, FDA medical equipment classifications, and examples of simple medical equipment classifications like diagnostic equipment, monitoring equipment, and therapeutic equipment. Diagnostic equipment includes medical imaging technologies like X-rays, CT scans, ultrasound, and MRI. Monitoring equipment includes patient monitors. Therapeutic equipment includes hemodialysis machines, radiotherapy, and rehabilitation equipment.
Biomedical Engineering (Multi-Choice Questions) - Mathankumar.S (VMKVEC)Mathankumar S
This document contains a 40 question multiple choice technical skills assessment test on biomedical engineering topics administered to students. The test covers subjects like anatomy, medical devices, imaging modalities, and more. Each question provides 4 answer choices with only one correct option. Students must select the right answer for each question. Upon completion, tutors will score the test and provide feedback to evaluate students' understanding of key biomedical engineering concepts.
Unit 1 DIP Fundamentals - Presentation Notes.pdfsdbhosale860
This document discusses the fundamentals of digital image processing. It begins by defining a digital image and explaining that digital image processing involves processing digital images using a computer. It then outlines 12 fundamental steps in digital image processing, including image acquisition, enhancement, restoration, compression, and pattern classification. Finally, it describes the typical components of an image processing system, including sensors, digitizers, computers, software, storage, and specialized hardware.
This document discusses digital graphics technology, describing features of vector and bitmap images. Vector images are resolution-independent and scalable without quality loss, using mathematical expressions to represent lines and shapes. Bitmap images are made up of pixels that lose quality when resized. The document provides examples of how vector and bitmap images differ when resized, and discusses image capturing, output methods for print and screen, storage considerations like file size and organization, and naming conventions.
This document summarizes various topics related to image processing including image data types, file formats, acquisition, storage, processing, communication, display, and enhancement techniques. It discusses key concepts such as image fundamentals, color models, resolution, bit depth, file formats like JPEG, GIF, TIFF, compression techniques including lossless, lossy, intraframe, interframe, and algorithms like run length encoding and Shannon-Fano coding. Image enhancement topics covered are point processing, spatial filtering, and color image processing.
Computer displays are made up of grids of small rectangular pixels that together form images. The smaller and closer together the pixels are, the higher the display's resolution and image quality. However, higher resolution requires larger file sizes to store more pixel data. Common file formats for raster graphics include BMP, PNG, GIF, TIFF and JPEG, which use different types and levels of compression to reduce file sizes. Compression can decrease file sizes but may also lower image quality or slow opening times if decompression is required. Optimization aims to improve how efficiently systems use resources like processing time, memory and power.
Pixel resolution determines the number of distinct pixels that can be displayed. Vector graphics use geometrical primitives based on mathematical expressions, while raster graphics represent images as a grid of pixels.
File formats specify how bits are used to encode image information. Common formats include GIF for images with a limited color palette, JPEG for photographic images using lossy compression, TIFF for bitmaps, EPS for vector graphics and bitmaps, BMP for Windows graphics, PNG for truecolor images, and PSD for layered Photoshop files.
Data compression reduces file size by eliminating statistical redundancy (lossless) or removing marginally important information (lossy). Image capture devices like digital cameras and scanners convert images to digital formats,
Standards and procedure in digitization and digital preservationCandy Husmillo
There are some standards for aspects of digitization and digital archiving, such as ISO standards for digitizing records and using PDF format for long-term preservation. However, standards are limited and there are no formal standards governing digital image capture, processing, and storage. Best practices have been developed instead. Common terms and concepts in digitization include masters and derivatives, resolution, file formats, compression, and optical character recognition. Considerations for successful digital archiving include quality, persistence, interoperability, and planning for future technological changes.
This document provides an overview of digital image processing. It discusses key concepts like image types (intensity, binary, indexed, RGB), image file formats (TIFF, JPEG), image resolutions, and the steps involved in digital image processing. The MATLAB Image Processing Toolbox is also mentioned as a tool for performing operations on images like visualization, analysis, and processing. Edge detection is highlighted as an important but difficult task in digital image processing.
The document defines several key terms related to digital images and file formats:
1. Pixel resolution refers to the number of pixels that can be displayed horizontally and vertically on a screen or image, with higher resolutions showing more detail but requiring larger file sizes.
2. There are two main types of computer graphics - raster (bitmap) images composed of pixels, and vector images composed of geometric paths.
3. Common file formats for digital images include BMP, PNG, GIF, TIFF, JPG, PSD, PDF, EPS and AI. Each has advantages for different types of images and uses.
4. Data compression reduces file sizes by removing unnecessary information, and can be lossless or lossy
Pixels make up images on displays and their number determines resolution. Common file formats include BMP for bitmaps, PNG for lossless web images, GIF for animations and logos with 256 colors, TIFF for publishing, JPEG for photos, PSD for Photoshop, PDF for documents, EPS for encapsulated PostScript, and AI for Adobe Illustrator. File compression reduces file sizes using algorithms, while digital asset management involves ingesting, cataloging, storing, and distributing digital assets like photos.
Pixels are the tiny dots that make up images on screens. The display resolution is the number of pixels that can be shown. Common file formats include BMP for bitmaps, PNG for lossless web images, GIF for simple images and animations with 256 colors, TIFF for professional photos, JPEG for digital camera photos, PSD for Photoshop files, PDF for documents, EPS for graphics, and AI for Adobe Illustrator files. File compression reduces file sizes using algorithms, while digital asset management involves ingesting, cataloging, storing and distributing digital media like photos and videos.
The document discusses image processing and describes its goals, applications, and system requirements. It defines image processing as altering existing images in a desired manner to extract important features and provide machine understanding. It provides examples of image processing applications like remote sensing, medical imaging, and character recognition. The proposed system allows users to modify images through tools for compression, rotation, resizing pixels and edge detection, and can process various file formats. Hardware requirements include at least 80GB storage, 512MB RAM, and a Pentium processor, while software requirements include Windows OS, Java/Swing technologies, Apache Tomcat server, and an Oracle or Access backend database.
This document summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They are easy to create but large in file size. Vectors use mathematical expressions to represent shapes and objects and are smaller in file size, but more difficult to create. Factors like compression and resolution can impact image quality. Both scanning and digital photography are discussed as methods to capture images, each with advantages and disadvantages. Common file formats, programs used, and organizing digital assets are also summarized.
This document provides an overview of image compression. It discusses what image compression is, why it is needed, common terminology used, entropy, compression system models, and algorithms for image compression including lossless and lossy techniques. Lossless algorithms compress data without any loss of information while lossy algorithms reduce file size by losing some information and quality. Common lossless techniques mentioned are run length encoding and Huffman coding while lossy methods aim to form a close perceptual approximation of the original image.
The document defines key technical terms related to digital images and computer graphics:
1. Pixels are the smallest controllable elements that make up a digital image on screen, and resolution refers to the total number of pixels that can be displayed horizontally and vertically.
2. Raster images are composed of pixels in a grid, while vector images use mathematical relationships between points and paths.
3. Common file formats include BMP, PNG, GIF, TIFF, JPG, PSD, PDF, EPS and AI, each suited to different types of images and uses.
4. Data compression reduces file size by identifying and removing statistical or unnecessary information from an image, which can be either lossless or loss
This document summarizes image processing techniques in the Android environment. It discusses compressed, saturated, and cropped images created using mathematical operations and techniques like JPEG lossy compression. It also covers adding text to images and adjusting brightness/contrast. Key aspects of image processing like compression, techniques like JPEG, and performance metrics for evaluating Android apps like CPU usage, memory usage, and GPU are overviewed.
The document discusses various topics related to digital images and file formats:
1. It defines pixels and resolution, which refer to the smallest controllable elements of an image and the number of pixels that can be displayed horizontally and vertically.
2. It summarizes several common file formats (BMP, PNG, GIF, TIFF, JPG, PSD, PDF, EPS, AI) and what types of images they are best suited for.
3. It provides brief explanations of compression, image capturing devices, optimizing, storage and asset management as they relate to digital images.
Image resolution is measured by the detail an image holds, which is quantified by how close lines can be to each other and still be visible. Pixel art is a form of digital art created by editing images on the pixel level. Vector graphics use geometrical primitives and mathematical expressions to represent images, while raster graphics represent images as a grid of pixels in an image file. Common file formats for raster graphics include BMP, PNG, GIF, TIFF, and JPEG, while PDF, EPS, and AI are examples of vector graphics file formats. Lossless data compression reduces file size by eliminating statistical redundancies without losing image data.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They are easy to create but large in file size. Vectors use mathematical expressions to represent shapes and are smaller in file size, but harder to create. They are best for logos, icons, and drawings. The report discusses advantages and disadvantages of each, as well as factors that affect quality like resolution and compression. It also covers capturing images through scanning and photography and organizing assets for projects.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and objects, allowing for scalability and smaller file sizes but requiring more time and skill. Both have advantages for certain uses, and quality can be affected by compression, resolution, and how images are captured through scanning or photography. Proper organization of graphic files is also discussed.
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2. 2/1/2015 2
Solving problems in biology and
medicine using engineering methods
and technology (e.g., research, design
and development of biomedical
instrumentation.)
3. Image is an Artifact that
reproduce the likeness of
some subjects usually a
physical object.
4. Images are pictures!
A picture that represents visual
information.
Used to save visual experiences.
A picture is worth a 1000 words…I
think more!!!
How are non-digital images stored?
Photographic film
Canvas/paint
Digitally
5. Imaging is the process of acquiring images.
Shorthand for image acquisition.
Process of sensing our surroundings and then
representing the measurements that are made in
the form of an image.
6. Passive imaging – employs energy sources
that are already present in the scene.
Active imaging – involves use of artificial
energy sources to probe our surroundings.
6
7. Passive imaging is subject to the limitations of
existing energy sources.
Passive Imaging
8. Active imaging is not restrictive in this way
but is invariably a more complicated &
expensive procedure.
Active imaging predominates in medical field,
where precise control over radiations sources
is essential.
Active imaging is also an important tool in
remote sensing.
8
Active Imaging
11. User Consortia (e.g., HL7)
Organizations (e.g., NEMA, IEEE)
US Government Agencies (e.g., ANSI, NIST)
Foreign Government Agencies (e.g., CEN)
United Nations (e.g., ISO, CCITT)
12. The name was changed to separate the standard
from the originating body
1991 - Release of Parts 1 and 8 of DICOM
1992 - RSNA demonstration, Part 8
1993 - DICOM Parts 1-9 approved,
RSNA demonstration of ALL parts
1994 - Part 10: Media Storage and File Format
1995 - Parts 11,12, and 13 plus Supplements
13. MAGN
ETOM
Information Management System
Storage, Query/Retrieve,
Study Component
Query/Retrieve, Patient & Study Management
Query/Retrieve
Results Management
Print Management
Media Exchange
LiteBox
16. Joint CEN-DICOM development
Medicom = DICOM
MIPS 95 work is underway with JIRA
IS&C Harmonization is also in progress
HL7 Harmonization continuing interest
New DICOM organization
Companies: NEMA and non-NEMA
ACR, ACC, CAP, ...
individuals
17. Networking is a critical component of all
medical imaging systems
Support for Open Communication Standards is a
MUST
DICOM is here, NOW
DICOM products exist on the market
DICOM is emerging as THE common protocol for
medical image communication - WORLD WIDE!
32. JPEG - Joint Photographic Experts Group
JPEG is designed with photographs in mind.
It is capable of handling all of the colors needed.
JPEGs have a lossy way of compressing images.
At a low compression value, this is largely not
noticeable, but at high compression, an image can
become blurry and messy. .jpg
33. JPEG cautions:
• Images with hard edges, high contrasts, angular areas, and
text suffer from JPEG compression.
• Scanned “natural” photographs do not lose much,
especially at High or Maximum quality.
• Only save finished images as JPEGs, every time you open
and save again, even if you don’t edit, you lose quality.
• Always keep the original non-JPEG version (the native .psd
format).
So why use JPEG?
• It is the best format for photographic images on the Web.
• It’s compression ability is very great.
35. GIF - Graphics Interchange Format
GIF is the most popular on the Internet, mainly because of its
small file size. It is ideal for small navigational icons and simple
diagrams and illustrations where accuracy is required, or
graphics with large blocks of a single color. The format is loss-
less, meaning it does not get blurry or messy.
The 256 color maximum is sometimes tight, and so it has the
option to dither, which means create the needed color by
mixing two or more available colors.
GIF use a simple technique called LZW compression to reduce
the file sizes of images by finding repeated patterns, but this
compression never degrades the image quality.
.GIF
36. 36
The GIF format is one of the most commonly used
graphic file formats, especially on the Internet.
The GIF format is exceedingly useful in that it can
contain animations. Its internal structure is such
that it can store multiple images and the controls to
make them appear as real time animation
animated GIF.
The GIF format also allows a special color as to be
specified as "using the background." This results in
the image looks like transparent
transparent GIF.
37. 37
Portable Network Graphic (PNG) which is
pronounced as “Ping”.
Alternative to GIF, a lossless compression
scheme is used.
Support three image type: true color,
grayscale, palette-based (8-bit).
JPEG supports the first 2.
GIF supports the 3rd one.
38. 38
Advantages
Better Compression
○ Deflate is an improved version of the Lempel-Ziv compression
algorithm.
Improve Interlacing
○ Display image quicker than Interlaced GIF.
True Color and Transparency
○ Support 16-bit (Grey scale) or 48-bit (True Color)
○ 16-bit for alpha channel (Transparency).
Gamma storage
○ Store the gamma setting of the platform of the creator.
Disadvantages
Not support by old browsers (Netscape 2,3,4 and IE 2,3,4)
39. TIFF - Tagged Image File Format
Widely used cross platform file format also designed for printing.
A bitmap image format.
TIFF supports lossless LZW compression which also makes it a
good archive format for Photoshop documents.
40. A popular format for grayscale images (8 bits/pixel)
Closely-related formats are:
PBM (Portable Bitmap), for binary images (1 bit/pixel)
PPM (Portable Pixelmap), for color images (24 bits/pixel)
- ASCII or binary (raw) storage
41. FITS - Flexible Image Transport System
Format of a FITS file (http://fits.gsfc.nasa.gov)
Primary Header: metadata describing
instrument, observation & file contents
Primary Data Array: array of 0-999
dimensions – usually a 2D image
+ none or more Extensions:
Array, ASCII Table or Binary Table, each with
Header
(New FITS-inspired XML format – VOTable)
42. 42
BMP - Bitmap Format
uses a pixel map which contains line by line information.
It is a very common format, as it got its start in Windows.
This format can cause an image to be super large.
43. Image Processing is any form of signal processing for
which our input is an image, such as photographs or
frames of video and our output can be either an image or
a set of characteristics or parameters related to the
image.
44. Image Processing generally refers to processing
of two dimensional picture and by two
dimensional picture we implies a digital image.
A digital image is an array of real or complex
numbers represented by a finite number of bits.
But now in these days optical and analog image
processing is also possible.
45. Is enhancing an image or extracting information
or features from an image.
Computerized routines for information extraction
(eg, pattern recognition, classification) from
remotely sensed images to obtain categories of
information about specific features.
46. Image processing are of two
aspects..
improving the visual appearance
of images to a human viewer
preparing images for
measurement of the features
and structures present.
2/1/2015 46
47. ❶ Acquisition of Image
Medical image data is acquired one slice at a time.
Resulting data set comprises n slices, each containing w x h
pixels.
Basic Steps for Image Processing
48. ❷ Data Storage
Array starts with the first row of the first slice and so on until the end of
the first slice.
Next, the array continues with the first row of the second slice, then the
second row of the second slice, and so on.
49. A single slice corresponds to a k
space plane acquired in real-time
The “K-Space” undergoes an Inverse
Fourier Transform.
Following this mathematical step,
we finally have an image
❸ Image Formation
50. ❹ Data Visualisation
Medical image data is commonly visualised by two
methods.
Reslicing
Surface rendering
51. Since the digital image is “invisible” it must be
prepared for viewing on one or more output
device (laser printer, monitor, etc.,)
It might be possible to analyze the image in the
computer and provide cues to the radiologists to
help detect important/suspicious structures (e.g.:
Computed Aided Diagnosis, CAD)
2/1/2015 51
Why do we need Image Processing
52. Image processing can be done using various
software's and languages such as:-
Language
VHDL
C/C++
Software
Matlab
Adobe Photoshop
Irfan view
How Image Processing is done?
53. 53
Early 1920’s: One of the first applications of digital
imaging was in the newspaper industry
The Bartlane cable picture
transmission service
Images were transferred by
submarine cable between London
and New York
Pictures were coded for cable
transfer and reconstructed at the
receiving end on a telegraph printer
Early digital image
54. Mid to late 1920’s: Improvements to the Bartlane
system resulted in higher quality images
Improved
digital image Early 15 tone digital
image
New reproduction processes
based on photographic
techniques
Increased number of tones in
reproduced images
55. 1960’s: Improvements in computing technology
and the onset of the space race led to a surge of
work in digital image processing
A picture of the moon taken
by the Ranger 7 probe
minutes before landing
1964: Computers used to
improve the quality of images of
the moon taken by the Ranger 7
probe
Such techniques were used in
other space missions including
the Apollo landings
56. 1970’s: Digital image processing begins to be
used in medical applications
Typical head slice CAT
image
1979: Sir Godfrey N. Hounsfield & Prof.
Allan M. Cormack share the Nobel Prize
in medicine for the invention of
tomography, the technology behind
Computerised Axial Tomography (CAT)
scans
57. 1980’s - Today: The use of digital image processing
techniques has exploded and they are now used for all kinds
of tasks in all kinds of areas
Image enhancement/restoration
Artistic effects
Medical visualisation
Industrial inspection
Law enforcement
Human computer interfaces
59. Primary purpose is to identify pathologic conditions.
Requires recognition of normal anatomy and
physiology.
Create image of body part
Disease Monitoring
60. Medical imaging is the technique and
process used to create images of
the human body or it’s parts for clinical
purposes .
Non-invasive visualization of internal
organs, tissue, etc.
61. Medical imaging has come a long way since 1895
when Röntgen first described a ‘new kind of ray’.
That X-rays could be used to display anatomical
features on a photographic plate was of immediate
interest to the medical community at the time.
Today a scan can refer to any one of a number of
medical-imaging techniques used for diagnosis and
treatment.
Medical Imaging using Ionising Radiations
62. The transmission and detection of X-rays still lies at the heart of
radiography, angiography, fluoroscopy and conventional
mammography examinations.
However, traditional film-based scanners are gradually being
replaced by digital systems
The end result is the data can be viewed, moved and stored without
a single piece of film ever being exposed.
Digital Systems
66. X-rays: A form of Electromagnetic
Energy travelling at the speed of
light.
Properties
*No mass *No charge *Energy
Wavelength – Range of 0.01 to 10
nanometer
67. X-rays: a form of electromagnetic energy
Travel at the speed of light
Electromagnetic spectrum
Gamma Rays X-rays
Visible light Infrared light
Microwaves Radar
Radio waves
68. X-Rays are associated with inner shell electrons
As the electrons decelerate in the target
through interaction, they emit electromagnetic
radiation in the form of x-rays.
patient is located between an x-ray source and
a film -> radiograph
cheap and relatively easy to use
potentially damaging to biological tissue
69. X-Rays - Visibility
Bones contain heavy atoms -> with many electrons,
which act as an absorber of x-rays
Commonly used to image gross bone structure and
lungs
Excellent for detecting foreign metal objects
Main disadvantage -> Lack of anatomical structure
All other tissue has very similar absorption
coefficient for x-rays
70. Three things can happen
X-rays can:
Pass all the way through the body
Be deflected or scattered
Be absorbed
Where on this image
have x-rays passed
through the body
to the greatest degree?
71. X-rays Passing Through Tissue
Depends on the energy of the x-ray
and the atomic number of the tissue
Higher energy x-ray - more likely to
pass through
Higher atomic number - more likely
to absorb the x-ray
72. X-rays that pass through the body to
the film render the film dark (black).
X-rays that are totally blocked do not
reach the film and render the film
light (white).
Air = low atomic no. = x-rays get through
= image is dark
Metal = high atomic no. = x-rays blocked
= image is light (white)
How do x-rays passing through
the body create an image?
73. 5 - Basic Radiographic Densities
Air
Fat
Soft tissue/fluid
Mineral
Metal
1.
2.
3.
4.
5.
75. Computerized (Axial) Tomography
Introduced in 1972 by Hounsfield and Cormack
Natural progression from X-rays
Based on the principle that a three-dimensional object can be
reconstructed from its two dimensional projections
From 2D to 3D !
Radon again!
CT (or) CAT
76. • Johan Radon (1917) - Showed how a reconstruction from
projections was possible.
• Cormack (1963,1964) - Introduced Fourier transforms into the
reconstruction algorithms.
• Hounsfield (1972) - Invented the X-ray Computer scanner for
medical work, (which Cormack and Hounsfield shared a Nobel
prize).
• EMI Ltd (1971) - Announced development of the EMI scanner
which combined X-ray measurements and sophisticated
algorithms solved by digital computers.
77. measures the attenuation of
X-rays from many different angles
a computer reconstructs the
organ under study in a series of
cross sections or planes
combine X-ray pictures from
various angles to reconstruct 3D
structures
78. Linear advancement (slice by slice)
typical method
tumor might fall between ‘cracks’
takes long time
Helical movement
5-8 times faster
A whole set of trade-offs
79. 1. Scanning the patient
2. Data Acquisition
Tube and detector move
Multiple attenuation
measurements are taken
around object.
3. Image reconstruction
4. Image Display
5. Image archival (recording)
80. Conventional CT
Axial
Start/stop
1.X-ray tube and detector rotate 360°
2.Patient table is stationary with X-ray’s “on”
3.Produces one cross-sectional image
4. Once this is complete patient is moved to
next position
Process starts again at the beginning
1.X-ray tube and detector rotate 360°
2.Patient table moves continuously
With X-ray’s “on”
3.Produces a helix of image information
4.This is reconstructed into 30 to 1000 images
Volumetric CT
Helical or spiral CT
Continuous acquisition
83. Medical Applications Type of Tomography
Full body scan X-ray
Respiratory, digestive systems,
brain scanning
PET Positron Emission
Tomography
Respiratory, digestive systems. Radio-isotopes
Mammography Ultrasound
Whole Body Magnetic Resonance (MRI, NMR)
PET scan on the
brain showing
Parkinson’s
Disease
MRI and PET showing
lesions in the brain.
84. Non Medical Applications Type of Tomography
Oil Pipe Flow
Turbine Plumes
Resistive/Capacitance
Tomography
Flame Analysis Optical Tomography
ECT on industrial pipe flows
85. Significantly more data is collected
Superior to single X-ray scans
Far easier to separate soft tissues other than bone from one
another (e.g. liver, kidney)
Data exist in digital form -> can be analyzed quantitatively
Adds enormously to the diagnostic information
Used in many large hospitals and medical centers throughout
the world
86. significantly more data is collected
soft tissue X-ray absorption still relatively similar
still a health risk
MRI is used for a detailed imaging of anatomy – no X rays
involved.
87. 1979 “For the Development of
computer assisted tomography (CAT)”
– Hounsfield & Cormack
2003 “For the Discoveries
concerning magnetic resonance
imaging (MRI)” - Paul Lauterbur &
Peter Mansfield
88. Nuclear Magnetic Resonance (NMR) (or Magnetic
Resonance Imaging - MRI)
Most detailed anatomical information
High-energy radiation is not used, i.e. this is “safe
method”
Based on the principle of nuclear resonance
(medicine) Uses resonance properties of protons
MRI (or) NMR
89. Magnetic resonance imaging (MRI),
Magnetic resonance imaging (MRI), is a
non-invasive method used to render
images of the inside of an object. It is
primarily used in medical imaging to
demonstrate pathological or other
physiological alterations of living tissues.
90. Hydrogen nuclei(protons) under a strong magnetic field in
phase with one another and align with the field.
Relaxed protons induce a measurable radio signal.
1952
Main modality for image guided surgery.
Ability to discriminate between subtle surfaces.
Very safe.
--Not effective for bone scanning.
91. Positron Emission Tomography
Single Photon Emission
Computerized Tomography
recent technique
involves the emission of particles of
antimatter by compounds injected
into the body being scanned
follow the movements of the
injected compound and its
metabolism
reconstruction techniques similar to
CT - Filter Back Projection & iterative
schemes
92. •Positron Emission Tomography
(PET) is a nuclear medicine medical
imaging technique which produces
a three-dimensional image or map
of functional processes or
Metabolic Activities in the body.
93. 93
To conduct the scan, a short-lived radioactive tracer isotope,
which decays by emitting a positron, which also has been
chemically incorporated into a metabolically active molecule,
is injected into the living subject (usually into blood
circulation).
The data set collected in PET is much poorer than CT, so
reconstruction techniques are more difficult (see section
below on image reconstruction of PET).
94. the use of high-frequency sound (ultrasonic) waves to
produce images of structures within the human body
above the range of sound audible to humans (typically
above 1MHz)
piezoelectric crystal creates sound waves
aimed at a specific area of the body
change in tissue density reflects waves
echoes are recorded
95. Delay of reflected signal and amplitude determines the position of
the tissue
still images or a moving picture of the inside of the body
there are no known examples of tissue damage from conventional
ultrasound imaging
commonly used to examine fetuses in utero in order to ascertain
size, position, or abnormalities
also for heart, liver, kidneys, gallbladder, breast, eye, and major
blood vessels
96. by far least expensive
very safe
very noisy
1D, 2D, 3D scanners
irregular sampling -
reconstruction
problems
98. Mammography is a radiographic examination that is
specially designed for detecting early breast cancer,
yielding a significant improvement in breast cancer
survival.
Mammography has been used in clinical practice since 1927
in the diagnosis of breast abnormalities.
In the late 1950s, the pioneering work of Gershon – Cohen
and Egan demonstrated that even clinically occult cancers
of early detection of breast cancer by screening asymptotic
women. 98
99. Since the first mammography units (xeromammography
and screen-film mammography in the 1970’s) became
available, both the equipment and the examination
procedure have changed and progressed.
A high degree of accuracy was developed with this
technique to differentiate between Benign and
Malignant disease.
99
102. Improved detection efficiency
A linear dynamic range
Increased signal-to-noise ratio (SNR)
Excellent Image Handling
Data in Digital form
Computer Aided Detection
Compatibility with PACS and Telemammography
102
103. Early Detection Is Your
BEST PROTECTION
If breast cancer is found and treated early, the five-year survival rate is 98
percent.
The social prejudices and stigma associated in screening of breast is to be
sensitized.
The success of the scheme depends upon the involvement of radiologists
and lab attendants who have to handle with delicate and humane.
Another success of the scheme rests upon instead of bringing the people
to lab, the lab itself has to go in search of the patient. For which a handy
and portable mammogram has to developed for instant and hassle free
Service. 103
104. Portable Mammography
GE unveiled an impressive portable
mammography concept as part of a
portfolio of integrated technologies aimed
at combating cancer.
The SenoCase is mobile mammography
system which can be folded and easily
stored in a car boot.
104
105. According to GE, such portability could remove geographical barriers to
regular breast screening for many women on a global scale.
The system could also be more cost effective than conventional
mammography systems, making it more accessible to smaller practices
and clinics.
A standard field of view Cesium Iodide
detector
Similar image quality to a full-field digital
mammography system
A user-friendly interface, operable by a
single clinician
105
106. Digital Portable Mammography
model was preferred in employee
surveys.
Employee feedback confirmed
that Women Diagnostic Center
mammograms are more convenient,
private and familiar because
employees feel more comfortable.
106
107. Digital mammography has proven to be
an essential tool in the diagnosis,
treatment and fight against breast cancer.
And studies have shown that routine
mammograms can help reduce breast
cancer mortality.
The important thing is that you make
annual mammography screening a top
priority for yourself and the women you
care about.
107
108. As defined at the beginning of this chapter,
angiography refers to radiologic imaging of blood
vessels after injection of a contrast medium.
To visualize these low-contrast structures, contrast
media is injected by a catheter that is placed in the vessel
of interest.
Positive contrast media are more commonly used, but
there are instances when use of negative contrast media
is indicated. Highly specialized imaging equipment is
required for these procedures.
111. Fluoroscopy is a technique in which a
continuous beam of x-rays is used to produce
moving images.
It is used to show movement in the digestive
system (which may require ingestion of a
high-contrast liquid such as barium) and the
circulatory system (angiograms).
112. 112
X-ray transmitted trough patient
The photographic plate replaced by fluorescent screen
Screen fluoresces under irradiation and gives a live image
Older systems— direct viewing of screen
Screen part of an Image Intensifier system
Coupled to a television camera
Radiologist can watch the images “live” on TV-monitor; images can
be recorded
Fluoroscopy often used to observe digestive tract
Upper GI series, Barium Swallow
Lower GI series Barium Enema
114. 114
• AVOID USE OF DIRECT FLUOROSCOPY
• Directive 97/43Euratom Art 8.4.
In the case of fluoroscopy, examinations without an
image intensification or equivalent techniques are
not justified and shall therefore be prohibited.
• Direct fluoroscopy will not comply with BSS
Performance of diagnostic radiography and
fluoroscopy equipment and of nuclear medicine
equipment should be assessed on the basis of
comparison with the diagnostic reference levels
115. 115
Remote control systems
Not requiring the presence of
medical specialists inside the X
Ray room
Mobile C-arms
Mostly used in surgical theatres.
116. 116
Interventional radiology systems
Requires specific safety considerations.
In interventional radiology the physician
can be near the patient during the
procedure.
Multipurpose fluoroscopy systems
Can be used as a remote control system
or as a system to perform simple
interventional procedures
117. Techniques which are well established in traditional engineering
applications need new hardware and software to work efficiently in the
biomedical arena. Much of our work includes fusing multiples sources of
data, or fusing data with underlying models of movement or tissue
properties to improve predictions, sometimes with the development of
novel instrumentation.
Current applications are in cancer diagnosis and therapy, stroke
rehabilitation and orthopaedics. Recent projects have included monitoring
heat distribution and tissue changes from ultrasound images in cancer
therapy (HIFU), developing protocols and instrumentation to assess arm
movement (with immediate application in stroke rehabilitation), and
ultrasound and microwave measurements on soft tissue.
We are pursuing methods to integrate the detection of electrical as well as
mechanical properties of tissue. 117
118. Recognising abnormal states; adaptive stimulation
At present, stimulation is continuous and this gives poor battery usage and can cause
habituation.
The goal is to make the next generation of stimulators adaptable to particular patients
through demand driven stimulation - altering the pattern and duration of stimulation to
the brain's own signals.
Tremor in Parkinson's disease (PD) is clearly detectable in the beta wave brain activity (as
well of course from external instrumentation such as accelerometers), but its onset is
very rapid.
We have developed methods using autorgressive models, coherence measures and
Hidden Markov modelling to detect the change of state associated with onset of tremor
from signals received from implanted electrodes in the subthalmic nucelus (which is a
prime target for stimulation in PD patients).
More generic work in this area has developed HMM models to identify state transitions
between different regions to identify brain networks using MEG imaging. This work is
currently been demonstrated on resting state data but will soon be applied to tremor
patients.
118
119. MEG (Magneto encephalography) imaging and application to
chronic pain patients
MEG is the only technology suitable for functional imaging for DBS patients as they have
metal implanted in the skull so fMRI cannot be used. MEG uses a set of very sensitive
magnetic sensors placed around the head to detect the magnetic fields associated with the
neuronal activity.
Once the signal have been acquired, an image is formed using a technique known as beam
forming which uses them to reconstruct the sources within the brain, a technique known as
beam forming.
The signals acquired are typically with low signal to noise ratio, non-Gaussian distribution
and correlated. Beam forming is therefore challenging. It is particularly difficult for DBS
patients because artefacts arise from the coil of wire left beneath the burr hole (through
which wires are taken to the battery.
119
120. Microwave imaging to diagnose breast cancer
Microwaves are an attractive imaging method for finding breast
tumours as the contrast between healthy tissue and tumour is
very high. However the resolution is low.
We are working to improve the interpretation of the data
gathered from both phantoms and clinical images using
microwave clinical imaging system developed in Bristol
University.
A spin out company from Bristol University has one of the few
clinical systems in use worldwide, which has been used in trials
in Frenchay Hospital. This work is funded by EPSRC.
120
121. Imaging Modalities
Imaging for medical purposes involves the services of
radiologists, radiographers, medical physicists and
biomedical engineers working together as a team for
maximum output. This ensures the production of
high quality of radiological service with consequent
improvement of health care service delivery.
121
122. Technological advances have made human imaging possible at
scales from a single molecule to the whole body.
By linking the anatomical data collected with emerging imaging
technologies to computer simulations, researchers now can
form truly functional images of individual patients.
These images will allow physicians not only to see what a
patient’s organs look like but also how they are functioning
even at the smallest dimensions.
A major challenge is how to store, analyze, distribute,
understand and use the enormous amount of data associated
with thousands of images.
122
123. Biomedical engineering stands at the forefront of this effort
because its researchers are able to integrate the engineering
tools needed to solve the technological problems of image
analysis with the deeper knowledge of the underlying biological
mechanisms.
Already, members of the Department of Biomedical
Engineering, in close collaboration with the Departments of
Applied Mathematics and Statistics, Computer Science,
Electrical and Computer Engineering, and Radiology, have
pioneered the use of imaging technology in computational
anatomy, neuropsychiatry, computer-integrated surgery and
cardiac procedures.
123
124. Now, researchers are expanding their imaging efforts
into other modalities and organ systems.
Ultimately, their work will contribute to advancing
image-guided therapy and to the early diagnosis and
treatment of a host of disorders, including heart
disease and brain dysfunction.
124
125. Included in Medical Imaging Research
Creating new systems and methods for measuring and analyzing
imaging data in humans, developing mathematical and computational
approaches to compare data across individuals, and applying these
techniques to understand, diagnose and treat disease.
Using novel imaging techniques to provide information on three-
dimensional structure and function at the molecular, cellular, tissue,
organ and organism level.
Improving ways to image blood flow and cardiac motion with magnetic
resonance imaging, computed tomography, ultrasound and
fluoroscopy.
Finding and modeling the cerebral cortex to understand both normal
and abnormal shape and the relation to genetic and environmental
disease.
Developing bio-inspired algorithms for recognizing objects and
actions in video. 125
126. Research - Biomedical Imaging
New developments in biomedical imaging provide a window
into complex biological phenomena.
Imaging enables researchers to track the movements of
molecules, cells, fluids, gases, or sometimes even whole
organisms.
Imaging techniques such as x-ray crystallography and magnetic
resonance imaging can also yield information about important
biological structures from single proteins to the human brain.
The frontiers of biomedical imaging promise to make diagnosis
of disease more accurate and less invasive, and to improve our
understanding of disease.
126
127. Imaging research encompasses
Imaging of protein complexes involved in synaptic communication in the
brain
Fluorescence tagging of molecules involved in intracellular signalling
networks
Non-invasive imaging of cancer
Imaging of human movement using dynamic MR, motion capture systems,
and ultrasonic imaging
Molecular and biochemical imaging with PET, SPECT, and optical imaging
Three-dimensional medical imaging of blood flow, blood vessels, and
cardiovascular lesions
Functional human brain mapping
Strategies for fusing images across modalities (e.g., CT and MR)
Ultrasonic diagnostic technology in medicine
Computational analysis and reconstruction of complex imaging data
127