This document discusses advances in iterative reconstruction (IR) techniques for computed tomography (CT) imaging that have led to reductions in patient radiation dose without compromising image quality. IR is an alternative reconstruction method to the traditionally used filtered back projection that allows for the identification and subtraction of image noise. Studies have found that applying IR in a blend with FBP can reduce patient radiation doses by 20-50% on average compared to full-dose FBP alone, while maintaining diagnostic image quality. The degree of dose and noise reduction increases as the percentage of IR used in the blend is increased, up to a point where images may appear over-smoothed but still diagnostically acceptable.
A Novel Adaptive Denoising Method for Removal of Impulse Noise in Images usin...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Hybrid Speckle Noise Reduction Method for Abdominal Circumference Segmentatio...IJECEIAES
Fetal biometric size such as abdominal circumference (AC) is used to predict fetal weight or gestational age in ultrasound images. The automatic biometric measurement can improve efficiency in the ultrasonography examination workflow. The unclear boundaries of the abdomen image and the speckle noise presence are the challenges for the automated AC measurement techniques. The main problem to improve the accuracy of the automatic AC segmentation is how to remove noise while retaining the boundary features of objects. In this paper, we proposed a hybrid ultrasound image denoising framework which was a combination of spatial-based filtering method and multiresolution based method. In this technique, an ultrasound image was decomposed into subbands using wavelet transform. A thresholding technique and the anisotropic diffusion method were applied to the detail subbands, at the same time the bilateral filtering modified the approximation subband. The proposed denoising approach had the best performance in the edge preservation level and could improve the accuracy of the abdominal circumference segmentation.
A Study of Total-Variation Based Noise-Reduction Algorithms For Low-Dose Cone...CSCJournals
In low-dose cone-beam computed tomography, the reconstructed image is contaminated with
excessive quantum noise. In this work, we examined the performance of two popular noisereduction
algorithms—total-variation based on the split Bregman (TVSB) and total-variation based
on Nesterov’s method (TVN)—on noisy imaging data from a computer-simulated Shepp–Logan
phantom, a physical CATPHAN phantom and head-and-neck patient. Up to 15% Gaussian noise
was added to the Shepp–Logan phantom. The CATPHAN phantom was scanned by a Varian OBI
system with scanning parameters 100 kVp, 4 ms, and 20 mA. Images from the head-and-neck
patient were generated by the same scanner, but with a 20-ms pulse time. The 4-ms low-dose
image of the head-and-neck patient was simulated by adding Poisson noise to the 20-ms image.
The performance of these two algorithms was quantitatively compared by computing the peak
signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR) and the total computational time. For
CATPHAN, PSNR improved by 2.3 dB and 3.1 dB with respect to the low-dose noisy image for the
TVSB and TVN based methods, respectively. The maximum enhancement ratio of CNR for
CATPHAN was 4.6 and 4.8 for TVSB and TVN respectively. For data for head-and-neck patient,
the PSNR improvement was 2.7 dB and 3.4 dB for TVSB and TVN respectively. Convergence
speed for the TVSB-based method was comparatively slower than TVN method. We conclude that
TVN algorithm has more desirable properties than TVSB for image denoising.
A Novel Adaptive Denoising Method for Removal of Impulse Noise in Images usin...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Hybrid Speckle Noise Reduction Method for Abdominal Circumference Segmentatio...IJECEIAES
Fetal biometric size such as abdominal circumference (AC) is used to predict fetal weight or gestational age in ultrasound images. The automatic biometric measurement can improve efficiency in the ultrasonography examination workflow. The unclear boundaries of the abdomen image and the speckle noise presence are the challenges for the automated AC measurement techniques. The main problem to improve the accuracy of the automatic AC segmentation is how to remove noise while retaining the boundary features of objects. In this paper, we proposed a hybrid ultrasound image denoising framework which was a combination of spatial-based filtering method and multiresolution based method. In this technique, an ultrasound image was decomposed into subbands using wavelet transform. A thresholding technique and the anisotropic diffusion method were applied to the detail subbands, at the same time the bilateral filtering modified the approximation subband. The proposed denoising approach had the best performance in the edge preservation level and could improve the accuracy of the abdominal circumference segmentation.
A Study of Total-Variation Based Noise-Reduction Algorithms For Low-Dose Cone...CSCJournals
In low-dose cone-beam computed tomography, the reconstructed image is contaminated with
excessive quantum noise. In this work, we examined the performance of two popular noisereduction
algorithms—total-variation based on the split Bregman (TVSB) and total-variation based
on Nesterov’s method (TVN)—on noisy imaging data from a computer-simulated Shepp–Logan
phantom, a physical CATPHAN phantom and head-and-neck patient. Up to 15% Gaussian noise
was added to the Shepp–Logan phantom. The CATPHAN phantom was scanned by a Varian OBI
system with scanning parameters 100 kVp, 4 ms, and 20 mA. Images from the head-and-neck
patient were generated by the same scanner, but with a 20-ms pulse time. The 4-ms low-dose
image of the head-and-neck patient was simulated by adding Poisson noise to the 20-ms image.
The performance of these two algorithms was quantitatively compared by computing the peak
signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR) and the total computational time. For
CATPHAN, PSNR improved by 2.3 dB and 3.1 dB with respect to the low-dose noisy image for the
TVSB and TVN based methods, respectively. The maximum enhancement ratio of CNR for
CATPHAN was 4.6 and 4.8 for TVSB and TVN respectively. For data for head-and-neck patient,
the PSNR improvement was 2.7 dB and 3.4 dB for TVSB and TVN respectively. Convergence
speed for the TVSB-based method was comparatively slower than TVN method. We conclude that
TVN algorithm has more desirable properties than TVSB for image denoising.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A Novel Approach For De-Noising CT Imagesidescitation
In this modern times and age, digital images play a
significant role in our day to-day life. Digital images are
utilized in a wide range of fields like medical, business and
more .Digital images play a vital part in the medical field in
which it has been utilized to analyze the anatomy. These
medical images are used in the identification of different
diseases. Regrettably, the medical images have noises due to
its different sources in which it has been produced.
Confiscating such noises from the medical images is extremely
crucial because these noises may degrade the quality of the
images and also baffle the identification of the
disease. Hence, de-noising of medical images is indispensable.
In this paper we demonstrate the implementations of de-
noising algorithm on CT images. The proposed technique has
4 processing stages. In the first stage the CT brain image is
acquired to MATLAB7.5. After acquisition the CT image is
given to preprocessing stage. Here the film artifacts are
removed. In the third stage, the high frequency components
and noise are removed from the CT image using median filter,
mean filter and Wiener filter
Digital Tomosynthesis: Theory of OperationCarestream
Digital Tomosynthesis (DT) is a new radiographic imaging technique that is revived from the nearly century-old traditional film-screen tomography. This rejuvenation is all made possible by the recent advances in high frame-rate, high-sensitivity flat-panel digital radiographic detector, rapid pulsed-exposure sequence-capable high-frequency x-ray generator, the widely available and low-cost computer GPU processing power, and the precision motion controls built in the digital radiography system hardware. Read the white paper.
Lung Nodule Segmentation in CT Images using Rotation Invariant Local Binary P...IDES Editor
As the lung cancer is the leading cause of cancer
death in the medical field, Computed Tomography (CT) scan
of the thorax is widely applied in diagnoses for identifying
the lung cancer. In this paper, a technique of rotation invariant
with Local Binary Pattern (LBP) for segmentation of various
lung nodules from the Lung CT cancer data sets is used. This
is tested on various lung data sets from teaching files of
Casimage database and National Cancer Institute (NCI) of
National Biomedical Imaging Archive (NBIA). The results
show the segmented nodules with clear boundaries, which is
helpful in diagnosis of lung cancer. Further, the results are
compared with the watershed segmentation method, which
shows that LBP based method yields better segmentation
accuracy.
An Ultrasound Image Despeckling Approach Based on Principle Component AnalysisCSCJournals
An approach based on principle component analysis (PCA) to filter out multiplicative noise from ultrasound images is presented in this paper. An image with speckle noise is segmented into small dyadic lengths, depending on the original size of the image, and the global covariance matrix is found. A projection matrix is then formed by selecting the maximum eigenvectors of the global covariance matrix. This projection matrix is used to filter speckle noise by projecting each segment into the signal subspace. The approach is based on the assumption that the signal and noise are independent and that the signal subspace is spanned by a subset of few principal eigenvectors. When applied on simulated and real ultrasound images, the proposed approach has outperformed some popular nonlinear denoising techniques such as 2D wavelets, 2D total variation filtering, and 2D anisotropic diffusion filtering in terms of edge preservation and maximum cleaning of speckle noise. It has also showed lower sensitivity to outliers resulting from the log transformation of the multiplicative noise.
Bone Suppression for Chest Radiographic ImagesCarestream
Learn about Carestream's Bone Suppression Software and how it's used to aid in the detection of lung diseases.
For more information on Carestream's software solutions, please visit http://carestream.com/software
An adaptive threshold segmentation for detection of nuclei in cervical cells ...csandit
PAP smear test is the most efficient and easy procedure to detect any abnormality in cervical
cells. It becomes difficult for the cytologist to analyse a large set of PAP smear test images
when there is a rapid increase in the incidence of cervical cancer. On the replacement, image
analysis could swap manual interpretation. This paper proposes a method for the detection of
cervical cells in pap smear images using wavelet based thresholding. First, Wiener filter is used
for smoothing to suppress the noise and to improve the contrast of the image. Second, optimal
threshold is been obtained for segmenting the cell by various Wavelet shrinkage techniques like
VisuShrink, BayesShrink and SureShrink thresholding which segment the foreground from the
background and detect cell component like nucleus from the clustered cell images. From the
results, it is proved that the performance of the adaptive Wiener filter with combination of
SureShrink thresholding performs better in terms of threshold values and Mean Squared Error
than the other comparative methods. The succeeding research work can be carried out based on
the size of the segmented nucleus which therefore helps in differentiating abnormality among
the cells.
EVP Plus Software delivers state-of-the-art image processing for CR and DR sy...Carestream
Radiographic technologists expect a high degree of
automation and efficiency in the technology they use in their
daily workflow, which means they expect minimal interaction
with the technology’s modality software. At the same time,
radiologists also need the flexibility to specify their site’s
individualized diagnostic viewing preferences. The CARESTREAM DirectView EVP Plus Software successfully
overcomes this challenge for digital-projection radiography.
EVP Plus automatically processes and delivers diagnostic-quality DR and CR images to PACS, based on look preferences that can be uniquely specified by each site.
New Noise Reduction Technique for Medical Ultrasound Imaging using Gabor Filt...CSCJournals
Ultrasound (US) imaging is an important medical diagnostic method, as it allows the examination of several internal body organs. However, its usefulness is diminished by signal dependent noise known as speckle noise. Speckle noise degrades target detectability in ultrasound images and reduces contrast and resolution, affecting the ability to identify normal and pathological tissue. For accurate diagnosis, it is important to remove this noise from ultrasound images. In this study, a new filtering technique is proposed for removing speckle noise from medical ultrasound images. It is based on Gabor filtering. Specifically, a preprocessing step is added before applying the Gabor filter. The proposed technique is applied to various ultrasound images, and certain measurement indexes are calculated, such as signal to noise ratio, peak signal to noise ratio, structure similarity index, and root mean square error, which are used for comparison. In particular, five widely used image enhancement techniques were applied to three types of ultrasound images (kidney, abdomen and ortho). The main objective of image enhancement is to obtain a highly detailed image, and in that respect, the proposed technique proved superior to other widely used filters.
Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filterijtsrd
In this paper a new method for the enhancement of gray scale images is introduced, when images are corrupted by fixed valued impulse noise salt and pepper noise . The proposed methodology ensures a better output for low and medium density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter SMF , Decision Based Median Filter DBMF and Modified Decision Based Median Filter MDBMF etc. The main objective of the proposed method was to improve peak signal to noise ratio PSNR , visual perception and reduction in blurring of image. The proposed algorithm replaced the noisy pixel by trimmed mean value. When previous pixel values, 0's and 255's are present in the particular window and all the pixel values are 0's and 255's then the remaining noisy pixels are replaced by mean value. The gray-scale image of mandrill and Lena were tested via proposed method. The experimental result shows better peak signal to noise ratio PSNR , mean square error MSE and mean absolute error MAE values with better visual and human perception. Sonali Malviya | Prof. Anshuj Jain "Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19086.pdf
http://www.ijtsrd.com/engineering/computer-engineering/19086/analysis-psnr-of-high-density-salt-and-pepper-impulse-noise-using-median-filter/sonali-malviya
Contourlet Transform Based Method For Medical Image DenoisingCSCJournals
Noise is an important factor of the medical image quality, because the high noise of medical imaging will not give us the useful information of the medical diagnosis. Basically, medical diagnosis is based on normal or abnormal information provided diagnose conclusion. In this paper, we proposed a denoising algorithm based on Contourlet transform for medical images. Contourlet transform is an extension of the wavelet transform in two dimensions using the multiscale and directional filter banks. The Contourlet transform has the advantages of multiscale and time-frequency-localization properties of wavelets, but also provides a high degree of directionality. For verifying the denoising performance of the Contourlet transform, two kinds of noise are added into our samples; Gaussian noise and speckle noise. Soft thresholding value for the Contourlet coefficients of noisy image is computed. Finally, the experimental results of proposed algorithm are compared with the results of wavelet transform. We found that the proposed algorithm has achieved acceptable results compared with those achieved by wavelet transform.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A Novel Approach For De-Noising CT Imagesidescitation
In this modern times and age, digital images play a
significant role in our day to-day life. Digital images are
utilized in a wide range of fields like medical, business and
more .Digital images play a vital part in the medical field in
which it has been utilized to analyze the anatomy. These
medical images are used in the identification of different
diseases. Regrettably, the medical images have noises due to
its different sources in which it has been produced.
Confiscating such noises from the medical images is extremely
crucial because these noises may degrade the quality of the
images and also baffle the identification of the
disease. Hence, de-noising of medical images is indispensable.
In this paper we demonstrate the implementations of de-
noising algorithm on CT images. The proposed technique has
4 processing stages. In the first stage the CT brain image is
acquired to MATLAB7.5. After acquisition the CT image is
given to preprocessing stage. Here the film artifacts are
removed. In the third stage, the high frequency components
and noise are removed from the CT image using median filter,
mean filter and Wiener filter
Digital Tomosynthesis: Theory of OperationCarestream
Digital Tomosynthesis (DT) is a new radiographic imaging technique that is revived from the nearly century-old traditional film-screen tomography. This rejuvenation is all made possible by the recent advances in high frame-rate, high-sensitivity flat-panel digital radiographic detector, rapid pulsed-exposure sequence-capable high-frequency x-ray generator, the widely available and low-cost computer GPU processing power, and the precision motion controls built in the digital radiography system hardware. Read the white paper.
Lung Nodule Segmentation in CT Images using Rotation Invariant Local Binary P...IDES Editor
As the lung cancer is the leading cause of cancer
death in the medical field, Computed Tomography (CT) scan
of the thorax is widely applied in diagnoses for identifying
the lung cancer. In this paper, a technique of rotation invariant
with Local Binary Pattern (LBP) for segmentation of various
lung nodules from the Lung CT cancer data sets is used. This
is tested on various lung data sets from teaching files of
Casimage database and National Cancer Institute (NCI) of
National Biomedical Imaging Archive (NBIA). The results
show the segmented nodules with clear boundaries, which is
helpful in diagnosis of lung cancer. Further, the results are
compared with the watershed segmentation method, which
shows that LBP based method yields better segmentation
accuracy.
An Ultrasound Image Despeckling Approach Based on Principle Component AnalysisCSCJournals
An approach based on principle component analysis (PCA) to filter out multiplicative noise from ultrasound images is presented in this paper. An image with speckle noise is segmented into small dyadic lengths, depending on the original size of the image, and the global covariance matrix is found. A projection matrix is then formed by selecting the maximum eigenvectors of the global covariance matrix. This projection matrix is used to filter speckle noise by projecting each segment into the signal subspace. The approach is based on the assumption that the signal and noise are independent and that the signal subspace is spanned by a subset of few principal eigenvectors. When applied on simulated and real ultrasound images, the proposed approach has outperformed some popular nonlinear denoising techniques such as 2D wavelets, 2D total variation filtering, and 2D anisotropic diffusion filtering in terms of edge preservation and maximum cleaning of speckle noise. It has also showed lower sensitivity to outliers resulting from the log transformation of the multiplicative noise.
Bone Suppression for Chest Radiographic ImagesCarestream
Learn about Carestream's Bone Suppression Software and how it's used to aid in the detection of lung diseases.
For more information on Carestream's software solutions, please visit http://carestream.com/software
An adaptive threshold segmentation for detection of nuclei in cervical cells ...csandit
PAP smear test is the most efficient and easy procedure to detect any abnormality in cervical
cells. It becomes difficult for the cytologist to analyse a large set of PAP smear test images
when there is a rapid increase in the incidence of cervical cancer. On the replacement, image
analysis could swap manual interpretation. This paper proposes a method for the detection of
cervical cells in pap smear images using wavelet based thresholding. First, Wiener filter is used
for smoothing to suppress the noise and to improve the contrast of the image. Second, optimal
threshold is been obtained for segmenting the cell by various Wavelet shrinkage techniques like
VisuShrink, BayesShrink and SureShrink thresholding which segment the foreground from the
background and detect cell component like nucleus from the clustered cell images. From the
results, it is proved that the performance of the adaptive Wiener filter with combination of
SureShrink thresholding performs better in terms of threshold values and Mean Squared Error
than the other comparative methods. The succeeding research work can be carried out based on
the size of the segmented nucleus which therefore helps in differentiating abnormality among
the cells.
EVP Plus Software delivers state-of-the-art image processing for CR and DR sy...Carestream
Radiographic technologists expect a high degree of
automation and efficiency in the technology they use in their
daily workflow, which means they expect minimal interaction
with the technology’s modality software. At the same time,
radiologists also need the flexibility to specify their site’s
individualized diagnostic viewing preferences. The CARESTREAM DirectView EVP Plus Software successfully
overcomes this challenge for digital-projection radiography.
EVP Plus automatically processes and delivers diagnostic-quality DR and CR images to PACS, based on look preferences that can be uniquely specified by each site.
New Noise Reduction Technique for Medical Ultrasound Imaging using Gabor Filt...CSCJournals
Ultrasound (US) imaging is an important medical diagnostic method, as it allows the examination of several internal body organs. However, its usefulness is diminished by signal dependent noise known as speckle noise. Speckle noise degrades target detectability in ultrasound images and reduces contrast and resolution, affecting the ability to identify normal and pathological tissue. For accurate diagnosis, it is important to remove this noise from ultrasound images. In this study, a new filtering technique is proposed for removing speckle noise from medical ultrasound images. It is based on Gabor filtering. Specifically, a preprocessing step is added before applying the Gabor filter. The proposed technique is applied to various ultrasound images, and certain measurement indexes are calculated, such as signal to noise ratio, peak signal to noise ratio, structure similarity index, and root mean square error, which are used for comparison. In particular, five widely used image enhancement techniques were applied to three types of ultrasound images (kidney, abdomen and ortho). The main objective of image enhancement is to obtain a highly detailed image, and in that respect, the proposed technique proved superior to other widely used filters.
Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filterijtsrd
In this paper a new method for the enhancement of gray scale images is introduced, when images are corrupted by fixed valued impulse noise salt and pepper noise . The proposed methodology ensures a better output for low and medium density of fixed value impulse noise as compare to the other famous filters like Standard Median Filter SMF , Decision Based Median Filter DBMF and Modified Decision Based Median Filter MDBMF etc. The main objective of the proposed method was to improve peak signal to noise ratio PSNR , visual perception and reduction in blurring of image. The proposed algorithm replaced the noisy pixel by trimmed mean value. When previous pixel values, 0's and 255's are present in the particular window and all the pixel values are 0's and 255's then the remaining noisy pixels are replaced by mean value. The gray-scale image of mandrill and Lena were tested via proposed method. The experimental result shows better peak signal to noise ratio PSNR , mean square error MSE and mean absolute error MAE values with better visual and human perception. Sonali Malviya | Prof. Anshuj Jain "Analysis PSNR of High Density Salt and Pepper Impulse Noise Using Median Filter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19086.pdf
http://www.ijtsrd.com/engineering/computer-engineering/19086/analysis-psnr-of-high-density-salt-and-pepper-impulse-noise-using-median-filter/sonali-malviya
Contourlet Transform Based Method For Medical Image DenoisingCSCJournals
Noise is an important factor of the medical image quality, because the high noise of medical imaging will not give us the useful information of the medical diagnosis. Basically, medical diagnosis is based on normal or abnormal information provided diagnose conclusion. In this paper, we proposed a denoising algorithm based on Contourlet transform for medical images. Contourlet transform is an extension of the wavelet transform in two dimensions using the multiscale and directional filter banks. The Contourlet transform has the advantages of multiscale and time-frequency-localization properties of wavelets, but also provides a high degree of directionality. For verifying the denoising performance of the Contourlet transform, two kinds of noise are added into our samples; Gaussian noise and speckle noise. Soft thresholding value for the Contourlet coefficients of noisy image is computed. Finally, the experimental results of proposed algorithm are compared with the results of wavelet transform. We found that the proposed algorithm has achieved acceptable results compared with those achieved by wavelet transform.
E FFECTIVE P ROCESSING A ND A NALYSIS OF R ADIOTHERAPY I MAGESsipij
a-Si Electronic Portal Imaging Device (EPID) is an
important tool to verify the location of the radiat
ion
therapy beam with respect to the patient anatomy. B
ut, Electronic Portal Images (EPI) suffer from low
contrast. In order to have better in-treatment imag
es to extract relevant features of the anatomy, ima
ge
processing tools need to be integrated in the Radio
logy systems. The goal of this research work is to
inspect
several image processing techniques for contrast en
hancement of electronic portal images and gauge
parameters like mean, variance, standard deviation,
MSE, RMSE, entropy, PSNR, AMBE, normalised cross
correlation, average difference, structural content
(SC), maximum difference and normalised absolute
error (NAE) to study their visual quality improvem
ent. In addition, by adding salt and pepper noise,
Gaussian noise and motion blur, we calculate error
measurement parameters like Universal Image Quality
(UIQ) index, Enhancement Measurement Error (EME), P
earson Correlation Coefficient, SNR and Mean
Absolute error (MAE). The improved results point ou
t that image processing tools need to be incorporat
ed
into radiology for accurate delivery of dose
FusIon - On-Field Security and Privacy Preservation for IoT Edge Devices: Con...jamesinniss
FusIon - On-Field Security and Privacy Preservation for IoT Edge Devices: Concurrent Defense Against Multiple types of Hardware Trojan Attacks
Get more info here:
>>> https://bit.ly/38FXJav
Performance Analysis and Optimization of Nonlinear Image Restoration Techniqu...CSCJournals
Abstract: This paper is concerned with critical performance analysis of spatial nonlinear restoration techniques for continuous tone images from various fields (Medical images, Natural images, and others images).The performance of the nonlinear restoration methods is provided with possible combination of various additive noises and images from diversified fields. Efficiency of nonlinear restoration techniques according to difference distortion and correlation distortion metrics is computed.Tests performed on monochrome images, with various synthetic and real-life degradations, without and with noise, in single frame scenarios, showed good results, both in subjective terms and in terms of the increase of signal to noise ratio(ISNR) measure. The comparison of the present approach with previous individual methods in terms of mean square error, peak signal-to-noise ratio, and normalised absolute error is also provided. In comparisons with other state of art methods, our approach yields better to optimization, and shows to be applicable to a much wider range of noises. We discuss how experimental results are useful to guide to select the effective combination. Promising performance analysed through computer simulation and compared to give critical analysis.
Histogram Equalization for Improving Quality of Low-Resolution Ultrasonograph...TELKOMNIKA JOURNAL
A well-prepared abstract enables the reader to identify the basic content of a document quickly and accurately, to determine its relevance to their interests, and thus to decide whether to read the document in its entirety. The Abstract should be informative and completely self-explanatory, provide a clear statement of the problem, the proposed approach or solution, and point out major findings and conclusions. The Abstract should be 100 to 150 words in length. The abstract should be written in the past tense. Standard nomenclature should be used and abbreviations should be avoided. No literature should be cited. The keyword list provides the opportunity to add keywords, used by the indexing and abstracting services, in addition to those already present in the title. Judicious use of keywords may increase the ease with which interested parties can locate our article.
Chest radiograph image enhancement with wavelet decomposition and morphologic...TELKOMNIKA JOURNAL
Medical image processing algorithms significantly affect the precision of disease diagnostic
process. This makes it crucial to improve the quality of a medical image with the goal to enhance
perceivability of the points of interest in order to obtain accurate diagnosis of a patient. Despite the
reliance of various medical diagnostics on X-rays, they are usually plagued by dark and low contrast
properties. Sought-after details in X-rays can only be accessed by means of digital image processing
techniques, despite the fact that these techniques are far from being perfect. In this paper, we implement
a wavelet decomposition and reconstruction technique to enhance radiograph properties, using a series of
morphological erosion and dilation to improve the visual quality of the chest radiographs for the detection of
cancer nodules.
This presentation was made on a thesis paper for my M.Sc academic curriculum. Color Guided Thermal image Super Resolution Technic is declared here.This paper is collected from IEEE.Publish in 2016.
A study of a modified histogram based fast enhancement algorithm (mhbfe)sipij
Image enhancement is one of the most important issues in low-level image processing. The goal of image
enhancement is to improve the quality of an image such that enhanced image is better than the original
image. Conventional Histogram equalization (HE) is one of the most algorithms used in the contrast
enhancement of medical images, this due to its simplicity and effectiveness. However, it causes the
unnatural look and visual artefacts, where it tends to change the brightness of an images. The Histogram
Based Fast Enhancement Algorithm (HBFE) tries to enhance the CT head images, where it improves the
water-washed effect caused by conventional histogram equalization algorithms with less complexity. It
depends on using full gray levels to enhance the soft tissues ignoring other image details. We present a
modification of this algorithm to be valid for most CT image types with keeping the degree of simplicity.
Experimental results show that The Modified Histogram Based Fast Enhancement Algorithm (MHBFE)
enhances the results in term of PSNR, AMBE and entropy. We use also the Statistical analysis to ensure
the improvement of the proposed modification that can be generalized. ANalysis Of VAriance (ANOVA) is
used as first to test whether or not all the results have the same average. Then we find the significant
improvement of the modification.
Dose Efficient Dual Energy Subtraction Radiography - Theory of OperationsCarestream
Dual energy digital radiography is an imaging technique that takes advantage of the differential, energy-dependent absorption properties of bone and soft tissue structures in human anatomy. By capturing two radiographic images of a patient in rapid succession, one at a relatively lower energy X-ray exposure and a second at a relatively higher energy, it is possible to mathematically derive a soft tissue-only image with bone structures removed, and a corresponding bone-only image. Read the white paper.
Framework for comprehensive enhancement of brain tumor images with single-win...IJECEIAES
Usage of grayscale format of radiological images is proportionately more as compared to that of colored one. This format of medical image suffers from all the possibility of improper clinical inference which will lead to error-prone analysis in further usage of such images in disease detection or classification. Therefore, we present a framework that offers single-window operation with a set of image enhancing algorithm meant for further optimizing the visuality of medical images. The framework performs preliminary pre-processing operation followed by implication of linear and non-linear filter and multi-level image enhancement processes. The significant contribution of this study is that it offers a comprehensive mechanism to implement the various enhancement schemes in highly discrete way that offers potential flexibility to physical in order to draw clinical conclusion about the disease being monitored. The proposed system takes the case study of brain tumor to implement to testify the framework.
1. INTRODUCTION
Iterative reconstruction was used to reconstruct images in Hounsfield’s first CT scanner. However, the ever increasing computational power required to apply IR to rapidly evolving CT technology,
restricted its application, and filtered back projection (FBP) was accepted as a means of reconstructing the images instead (Beister, Kolditz and Kalender, 2012). With the advent of faster computers,
research into applying Adaptive Iterative Reconstruction (IR) as a means to reduce patient dose has proved favourable with regards to image quality comparisons with FBP. This poster discusses the
advances of IR and how its applications have led to a measurable reduction in patient dose, while not compromising on image quality.
1. DISCUSSION
The results of the 2003 National Radiation Protection Board survey
found that CT examinations in the UK make up only 9% of medical
exposures, yet contribute to 47% of the total radiation dose
(Shrimpton et al, 2005), demonstrating a doubling in CT doses from
the previous ten years (Hart and Wall, 2004). This exponential
increase in dose is supported by Karpitschka et al, (2013) who
calculated that there has been a 12-fold increase in the amount of
CT scans performed in the UK in the last 25 years. The cancer
inducing effects of radiation are well known with the lifetime
cancer risk from CT scans being estimated at 2% (Silva et al, 2010).
With the advancement in CT technology and the growing
dependence on high dose procedures, it is apparent that patient
dose is of increasing concern, and reduction methods must be
researched.
According to Sagara et al, (2010), currently available dose-saving
techniques already implemented into CT has been hindered by the
limitations of FBP. Whilst lowering the tube current (mA) and
increasing rotation speed decreases patient dose; it also results in
increased image noise and inconsistencies in FBP reconstructions.
Modern computer technology allows for the implementation of IR
techniques which are capable of identifying and subtracting image
noise (Silva et al, 2010) without reducing spatial or contrast
resolution (Mitsumori et al, 2012).
Dose and Noise Reduction in CT through the Application of Adaptive Iterative Reconstruction
3. Appearances of IR
It is generally agreed upon that by applying IR, lower
doses without a compromise on image quality can be
achieved. Nevertheless; inherent image noise is
something that has been traditionally accepted and
expected in CT. The noise free appearance of the
iteratively reconstructed images may not be acceptable
or appealing to radiologists initially (Hara et al, 2009), as
reports have concluded these images may appear to be
over-smooth (Silva et al, 2010) or have a waxy texture
(Mitsumori et al, 2012); and could be deemed to be
artifacts themselves. Singh et al, (2010) reported a
blotchy pixilation and decreased sharpness or irregular
margin of cysts, solid organs and vessels in their studies;
yet these did not render the reconstructed images to be
diagnostically unacceptable.
2. What is IR?
Different vendors use different methods of IR processes,
but all follow the same basic principle. The initial
information from the FBP is used as a ‘building block’ and
the value of each pixel is transformed to a new estimated
value (Silva et al, 2010). These pixels are forward projected
to produce estimated projections which are then compared
to the measured values (Karpitschka et al, 2013). After a
correction factor is obtained, this is back-projected across
the original estimated values to produce new estimated
vales. The process is repeated, correcting the data by
reducing the difference between the two projections
(Hsieh, 2009), until the estimates match these measured
values , or a fixed number of iterations are reached
(Beister, Kolditz and Kalender, 2012). (Fig. 1) This software
is known as Adaptive Statistical Iterative Reconstruction
(ASIR) on GE scanners, and Image Reconstruction in Image
Space (IRIS) on Siemens. GE has followed on with a more
complex model based iterative reconstruction method,
known as ‘VEO’ (Beister, Kolditz and Kalender, 2012), which
claims to allow for ‘ultra low dose’ scanning with increased
spatial resolution (Thibault 2011).
4. Blending
IR can be applied to a low dose CT scan as a linear mixture or
a ‘blend’ of IR and FBP; a compromise intended to produce a
more typical CT image with significantly reduced dose (Hara
et al, 2009). These reports of unfamiliar over-smoothening
are based on studies where between 70-100% IR was applied
to low dose FBP. The percentage values can typically be
adjusted in 10% increments: as the percentage of IR
increases, image noise decreases (Fig.2), therefore
controlling the amount of over-smoothing (Silva, et al.,
2010), resulting in images more familiar to radiologists
(Mitsumori et al, 2012).
5. Noise and Dose Reduction
Results from multiple studies comparing both subjective and
objective research give promise for the use of IR in dose saving. In
the subjective studies, radiologists who were blinded to the
reconstruction properties of the scan were asked to score on
image quality and diagnostic acceptability. This was performed
alongside objective research, where a region of interest (ROI) tool
was used on patients or phantoms to measure noise.
Hara et al, (2009) measured noise as being reduced by 75% with
100% IR on low dose CT, with dose halved with 50% IR. Images
were comparable with full dose FBP when 30% IR was applied.
However it produced an average reduction of 44% in dose (Fig 3.).
Conversely, Singh et al, (2010) reported that low dose 100% FBP
scans were suboptimal, whilst those that had 30% and 50% IR
applied, were acceptable with no compromise on vessel or lesion
conspicuity. Both Mitsumori et al, (2012) and Karpitschka et al,
(2013), achieved an average of 40% dose reduction using 50% IR;
neither reporting an appreciable reduction in image quality. A 28%
average dose reduction with comparable image quality to full dose
FBP while using 40% IR was reported by Sagara et al, (2010) and
31.5% average dose reduction by Desai et al, (2012) with the
application of 30% IR, giving a 33.3% reduction in noise. This
presents the conclusion that as the percentage of IR increases,
dose and noise decreases, without compromise on image quality
or diagnostic acceptability (fig 4) when used with the best agreed
upon blend of FBP.
Applying IR techniques has been shown to lower the increased
noise and photon starvation artefact created when imaging obese
patients (Silva et al, 2010). Desai et al, (2012) supports this when
researching the application of IR on patients weighing ≥91 kg
where IR gave at least comparable diagnostic acceptability to FBP,
but with noise and dose reductions of 50% and 21.4%,
respectively, on average for this group.
Low dose procedures currently in clinical use, such as those for
renal stones, coronary calcium plaques and colonography, allow
for increased image noise outside of the area of interest. However,
applying IR has shown a reduction in image noise can demonstrate
the anatomy of the solid organs traditionally obscured by image
noise on such scans, while also potentially lowering dose by a
further 25%, or even halving it in the case of CT colonography
(Silva et al, 2010).
A potential further application suggested by Hara et al, (2009) was
the increased resolution of typically noisy thin slices and their
diagnostic potential when reconstructed with IR for the detection
and characterisation of lesions which may have been missed on
thicker slices.
6. CONCLUSION
The evidence suggests that with an advancement in computer capabilities and an adaptive approach to iterative reconstruction, IR is a feasible method when used in the correct blend with FBP to
lower patient radiation dose and reduce the noise that would be incident on the resultant FBP image, without compromising on, and even in some instances improving, on image quality. In the future
it may be possible to further reduce dose with higher percentages of IR applied to images as they become more acceptable to radiologists, and as further advancements in faster computer technology
and more advanced IR techniques becomes available such as Model Based Iterative Reconstruction.
Fig 1. Schematic of the IR process (Beister, Kolditz and Kalender, 2012).
Fig 3. Example of low dose images which were reconstructed with FBP (A&C) showing
noisy images compared against the same images reconstructed with IR (B&D)
demonstrating a smoother appearance (Beister, Kolditz and Kalender, 2012.
Fig 2. Diagram showing the appearances of applying IR in increasing increments (Silva et al,
2010) .
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Fig 4. 3 images of the same slice with different doses and reconstruction methods applied. A is a 100% FBP image demonstrating more
noise than image B which has had IR applied, and has comparable image quality and diagnostic acceptability to C which is a full dose
scan with FBP (Hara et al, 2009)