Image reconstruction in CT is mostly a mathematical process however, this presentation tries to explain the complicated process of image reconstruction in a visual way, mainly focusing om Filtered back projection, Iterative Reconstruction and AI based image reconstruction.
This slide best explains the introduction of CT, basis and types of CT image reconstructions with detailed explanation about Interpolation, convolution, Fourier slice theorem, Fourier transformation and brief explanation about the image domain i.e digital image processing.
Quality Assurance Programme in Computed TomographyRamzee Small
Introduction to Computed Tomography
Basic description of the components of a CT System
Introduction to Quality Assurance
Quality Assurance and Quality Control Tests in Computed Tomography base on frequency
Objective of QA/QC Test
Image reconstruction in CT is mostly a mathematical process however, this presentation tries to explain the complicated process of image reconstruction in a visual way, mainly focusing om Filtered back projection, Iterative Reconstruction and AI based image reconstruction.
This slide best explains the introduction of CT, basis and types of CT image reconstructions with detailed explanation about Interpolation, convolution, Fourier slice theorem, Fourier transformation and brief explanation about the image domain i.e digital image processing.
Quality Assurance Programme in Computed TomographyRamzee Small
Introduction to Computed Tomography
Basic description of the components of a CT System
Introduction to Quality Assurance
Quality Assurance and Quality Control Tests in Computed Tomography base on frequency
Objective of QA/QC Test
principle of ct scanner
generations
scanning motion
EMI unit
xray beam
x ray tube
advantages
disadvantages
in this you PPT got clear idea about generation of ct
if you have any doubt text me
insta ID - ___sadham_____
it includes generations and advancement in CT. In generations fifth generation CT is described in detail.
UFC detector, stellar detectors and gemstone detector is also described
straton x-ray tube, MRC, LIMAX and aquillion one xray tube
different techniques used in CT
dual energy CT is also described
this slide sharer contents are basic principle of CT fluoroscopy , software and hardware parts of equipment and image aqua cation and radiation dose comparison and videos related to equipment .
Image Quality, Artifacts and it's Remedies in CT-Avinesh ShresthaAvinesh Shrestha
CT is one of the frequently used diagnostic imaging modalities in Radiology. Knowledge about image quality and artifacts is essential when diagnosing a patient with the help of CT images. Moreover, Radiology Technologist's should be very well aware about the ways to identify and eliminate or minimize the artifacts in CT for better image quality.
principle of ct scanner
generations
scanning motion
EMI unit
xray beam
x ray tube
advantages
disadvantages
in this you PPT got clear idea about generation of ct
if you have any doubt text me
insta ID - ___sadham_____
it includes generations and advancement in CT. In generations fifth generation CT is described in detail.
UFC detector, stellar detectors and gemstone detector is also described
straton x-ray tube, MRC, LIMAX and aquillion one xray tube
different techniques used in CT
dual energy CT is also described
this slide sharer contents are basic principle of CT fluoroscopy , software and hardware parts of equipment and image aqua cation and radiation dose comparison and videos related to equipment .
Image Quality, Artifacts and it's Remedies in CT-Avinesh ShresthaAvinesh Shrestha
CT is one of the frequently used diagnostic imaging modalities in Radiology. Knowledge about image quality and artifacts is essential when diagnosing a patient with the help of CT images. Moreover, Radiology Technologist's should be very well aware about the ways to identify and eliminate or minimize the artifacts in CT for better image quality.
This PPT gives detailed information about Computer Graphics, Raster Scan System, Random Scan System, CRT Display, Color CRT Monitors, Input and Output Devices
Improving image resolution through the cra algorithm involved recycling proce...csandit
Image processing concepts are widely used in medical fields. Digital images are prone to a
variety of types of noise. Noise is the result of errors in the image acquisition process for
reconstruction that result in pixel values that reflect the true intensities of the real scenes. A lot
of researchers are working on the field analysis and processing of multi-dimensional images.
Work previously hasn’t sufficient to stop them, so they continue performance work is due by the
researcher. In this paper we contribute a novel research work for analysis and performance
improvement about to image resolution. We proposed Concede Reconstruction Algorithm (CRA)
Involved Recycling Process to reduce the remained problem in improvement part of an image
processing. The CRA algorithms have better response from researcher to use them
IMPROVING IMAGE RESOLUTION THROUGH THE CRA ALGORITHM INVOLVED RECYCLING PROCE...cscpconf
Image processing concepts are widely used in medical fields. Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process for
reconstruction that result in pixel values that reflect the true intensities of the real scenes. A lot of researchers are working on the field analysis and processing of multi-dimensional images. Work previously hasn’t sufficient to stop them, so they continue performance work is due by the researcher. In this paper we contribute a novel research work for analysis and performance improvement about to image resolution. We proposed Concede Reconstruction Algorithm (CRA)
Involved Recycling Process to reduce the remained problem in improvement part of an image processing. The CRA algorithms have better response from researcher to use them.
X-ray Nanotomography Imaging for Circuit Integrity AbhaySingh640
X-ray Nanotomography Imaging for Circuit Integrity :
The need for reliable and secure technological devices requires integrated circuits (ICs) that maintain integrity of the original design1. In order to keep costs low, ICs are often manufactured overseas2. Chip modifications, also called “Hardware Trojans” can be inserted in various phases of production, testing, and distribution, and be triggered later by pre-programmed timed or physical events, which can cause failure or compromise at key times during operation3. This can affect applications in fields as diverse as defense, aeronautic industry, consumer medical and financial records, and transportation security, for example. The authentication of IC chips to scan for Trojans can be complex because the type of modification can vary significantly, and is usually unknown in advance. Hence a thorough yet non destructive method for ensuring circuit integrity is required.
Using the transmission x-ray microscope on Beam Line 6-2 at the Stanford Synchrotron Radiation Lightsource, based on an Xradia lab model4, researchers from the University of Southern California Information Sciences Institute and Xradia Inc. have developed nanoscale computerized tomography (CT) methods to obtain nondestructive high resolution (30 nm) 3D images of integrated circuits that could be used to scan for defects and modifications. Because the ICs are very large compared with the microscope field of view (30 microns), complex methods for imaging the circuits and reconstruction of the 3D data were developed
X-rays were discovered in 1895 by the German physicist Wilhelm Conrad Röntgen,
who earned the Nobel Prize in Physics in 1901. Although their potential applications
in medical imaging diagnosis were clear from the beginning, the implementation of
the first X-ray computed tomography system was made in 1972 by Godfrey Newbold
Hounsfield (Nobel prize winner in 1979 for Physiology and Medicine), who constructed
the prototype of the first medical CT scanner and is considered the father of computed
tomography. CT was introduced into clinical practice into 1971 with a scan of a cystic
frontal lobe tumor on a patient at Atkinson Morley Hospital in Wimbledon (United
Kingdom). After this, CT was immediately welcomed by the medical community and
has often been referred to as the most important invention in radiological diagnosis, since
the discovery of X-rays [1].
The first applications of CT in an industrial context is traced back to the first 1980´s, in the
field of non destructive testing, where small number of slices of the object were visually
inspected. 3D quantitative industrial CT applications appeared in the later 1990s, with
simple volume and distance analysis [2]. Today, thanks to relevant improvements in both
hardware and software, CT has become a powerful and widely used tool among non
destructive techniques, capable of inspecting external and internal structures (without
destroying them) in many industrial applications. Development of more and more stable
X-ray sources and better detectors led to design of more complex CT system, providing
accurate geometrical information with micrometer accuracy. CT is widely used for
geometrical characterization of test objects, material composition determination, density
variation inspection etc. In a relative short time, CT is capable to produce a complete
three-dimensional model and tolerances of the scanned machined parts can be verified.
Because of the growing interest on precision in production engineering and an increasing
demand for quality control and assurance, CT is leading the field of manufacturing
and coordinate metrology. With respect to traditional techniques, CT systems have indisputable advantages: internal and external geometry can be acquired without
destroying the part, with a density of information much higher than common tactile and
optical coordinate measuring. A key parameter for reliability of the measurement process
is the establishment of measuring uncertainty. Since there are many influence parameters
in CT, uncertainty contributors in CT and standards dealing with quantification of CT
have not been completely established yet. The assessment of the uncertainty budget
becomes a challenge for all researchers
Chebyshev filter applied to an inversion technique for breast tumour detectioneSAT Journals
Abstract Microwave imaging has been extensively studied in the past several years as a new technique for early stage breast cancer detection. The rationale of microwave imaging for breast tumour detection is significant contrast in the dielectric properties of normal tissue and malignant tumours. However, in practice noise present from the environments during screening/examination degrades the quality of the image. Inaccurate reconstructed image caused false/misleading interpretation of the image which leads to inappropriate diagnose or treatment to the patient. In the simulation works, noise is added to imitate the actual environment scenario. The two-dimensional (2D) object that identical to breast model is developed using numerical simulation to imitate the breast model. A filter is integrated with an iterative inversion technique for breast tumour detection to eliminate the noise. To assess the effectiveness of this approach, we consider the reconstruction of the electrical parameter profiles of 2D objects from measurements of the transient total electromagnetic field data contaminated with noise. Additive white Gaussian noise is utilized to mimic the effect of random processes that occur in the nature. This paper presents the filter settings and characteristics that affect the reconstruction of the image in order to obtain the most reliable and closer to the actual image. Selection of filter settings or design is important in order to achieve desired signal, most accurate image and provide reliable information of the object. Chebyshev low pass filter is applied in the Forward-Backward Time-Stepping (FBTS) algorithm to filter the noisy data and to improve the quality of reconstructed image. Keywords: Chebyshev low pass filter, microwave imaging and breast tumour detection
Chebyshev filter applied to an inversion technique for breast tumour detectioneSAT Journals
Abstract Respiration Rate is one of the vital signs which require regular monitoring among diseased people. There are a number of medical devices developed to monitor human health condition among them RR monitor is one. The Respiration rate monitor is a device that measures the subject’s respiration rate non-invasively. The objective of the proposed work is to design and develop a low cost Respiration rate monitor for clinical applications. The main parameter to be used is the temperature of respired air i.e. both inspired and expired air. Hence this device uses Thermistor as the source sensor which will provide the temperature feedback of the inspired and expired air. The proposed work uses the ATMEL AT89S52 microprocessor with external ADC0809. The magnitude voltage during the inhalation and exhalation is converted into digital signal using ADC. The further process involves a peak detection technique. The number of peaks obtained in duration of one minute gives the Respiration Rate. The so obtained Respiration Rate is sent to the concerned physician’s cell phone through GSM modem. The device gives an alarm and sends request via SMS if there is tachyopnea and bradyapnea. Keywords: Respiratory Rate, Peak Detection, ADC, GSM, SM, Threshold.
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2. This presentation includes;
• Data acquisition and modes of data acquisition
• Digitizing an image
• Pixel and voxel
• CT numbers
• Image reconstruction and reconstruction algorithms
3. Data acquisition in CT
•A method by which the patient is scanned, and obtains
enough data for reconstruction.
4. Modes of data acquisition
1)Scanned projection
2)Basic axial acquisition
3)Helical (spiral) acquition
5. Digitizing an image
• The primary objective of digitizing an image is to convert an analog image
into numerical data for the processing by the computer.
• It includes following steps:
I. Scanning
II. Sampling
III. quantization
7. CT number
• Each pixel is displayed on the monitor as a level of brightness which
correspond to a range of CT numbers from -1000 to +3000.
• CT number = 𝑘
𝜇 𝑡−𝜇 𝜈
𝜇 𝑤
where,
• µt = attenuation coefficient of the tissue in the voxel under analysis
• µw = attenuation coefficient of water
• ‘k’ is a constant that determines the scale factor for the range of CT numbers
• When k is 1000, the CT numbers are called Hounsfield Units and range from -
1000 to +1000
9. Image reconstruction
•The process of using raw data to create an image is
called reconstruction.
•Image reconstruction is done with the combination of
complex computer algorithms, mathematical equations
and physics.
10. Reconstruction algorithms
• An algorithm is a finite set of unambiguous steps performed in a
prescribed sequence to solve a problem.
• In CT, reconstruction algorithms are used by the computer to
solve the many mathematical equations necessary for the
conversion of the information detector arrays to the information
suitable for image display.
12. Reconstruction algorithms
2. Filtered backprojection:
• Simple backprojection technique results in characterstic star-like
artifact.
• To eliminate this artifact, a mathematical filter is used in scanned
data before backprojection, and hence k/a filtered backprojection.
• The process of applying a filter function to a scanned data is
called convolution.
13. Reconstruction algorithms
3. Fourier transformation:
• Developed by 17th century mathematician Baron Jean Baptiste Joseph
Fourier.
• The Fourier transformation is a mathematical procedure for breaking down
a waveform into a series of sine and cosine functions of different
frequencies and amplitude.
14. Reconstruction algorithms
4. Ierative reconstruction:
•An iterative reconstruction starts with an assumption
and compares this assumption with measured values,
makes corrections to bring the two into agreement, and
then repeats this process over and over until the
assumed and measured values are same or within
acceptable limits.