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Computer Aided Autism Diagnosis Using Diffusion Tensor Imaging
Yaser A. Elnakieb;Mohamed T. Ali;Ahmed Soliman;Ali H. Mahmoud;Ahmed M. Shalaby;Norah Saleh Alghamdi;Mohammed Ghazal;Ashraf Khalil;Andrew Switala;Robert S. Keynton;Gregory Neal Barnes;Ayman El-Baz
Autism Spectrum Disorder (ASD), commonly known as autism, is a lifelong developmental disorder associated with a broad range of symptoms including difficulties in social interaction, communication skills, and restricted and repetitive behaviors. In autism spectrum disorder, numerous studies suggest abnormal development of neural networks that manifest itself as abnormalities of brain shape, functi...Show More
A Deep Learning-Based Cad System For Renal Allograft Assessment: Diffusion, Bold, And Clinical Biomarkers
Mohamed Shehata;Mohammed Ghazal;Hadil Abu Khalifeh;Ashraf Khalil;Ahmed Shalaby;Amy C. Dwyer;Ashraf M. Bakr;Robert Keynton;Ayman El-Baz
2020 IEEE International Conference on Image Processing (ICIP)
Year: 2020 | Conference Paper |
Cited by: Papers (5)
Recently, studies for non-invasive renal transplant evaluation have been explored to control allograft rejection. In this paper, a computer-aided diagnostic system has been developed to accommodate with an early-stage renal transplant status assessment, called RT-CAD. Our model of this system integrated multiple sources for a more accurate diagnosis: two image-based sources and two clinical-based ...Show More
A Comprehensive Framework For Accurate Classification of Pulmonary Nodules
Ahmed Shaffie;Ahmed Soliman;Hadil Abu Khalifeh;Mohammed Ghazal;Fatma Taher;Adel Elmaghraby;Robert Keynton;Ayman El-Baz
2020 IEEE International Conference on Image Processing (ICIP)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
A precise computerized lung nodule diagnosis framework is very important for helping radiologists to diagnose lung nodules at an early stage. In this manuscript, a novel system for pulmonary nodule diagnosis, utilizing features extracted from single computed tomography (CT) scans, is proposed. This system combines robust descriptors for both texture and contour features to give a prediction of the...Show More
A 3D CNN with a Learnable Adaptive Shape Prior for Accurate Segmentation of Bladder Wall Using MR Images
K. Hammouda;F. Khalifa;A. Soliman;H. Abdeltawab;M. Ghazal;M. Abou El-Ghar;A. Haddad;H. E. Darwish;R. Keynton;A. El-Baz
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
Year: 2020 | Conference Paper |
Cited by: Papers (12)
A 3D deep learning-based convolution neural network (CNN) is developed for accurate segmentation of pathological bladder (both wall border and pathology) using T2-weighted magnetic resonance imaging (T2W-MRI). Our system starts with a preprocessing step for data normalization to a unique space and extraction of a region-of-interest (ROI). The major stage utilizes a 3D CNN for pathological bladder ...Show More
A Novel Framework for Grading Autism Severity Using Task-Based FMRI
Reem Haweel;Omar Dekhil;Ahmed Shalaby;Ali Mahmoud;Mohammed Ghazal;Ashraf Khalil;Robert Keynton;Gregory Barnes;Ayman El-Baz
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
Year: 2020 | Conference Paper |
Cited by: Papers (9)
Autism is a developmental disorder associated with difficulties in communication and social interaction. Currently, the gold standard in autism diagnosis is the autism diagnostic observation schedule (ADOS) interviews that assign a score indicating the level of severity for each individual. However, current researchers investigate developing objective technologies to diagnose autism employing brai...Show More
A New System for Lung Cancer Diagnosis based on the Integration of Global and Local CT Features
Ahmed Shaffie;Ahmed Soliman;Hadil Abu Khalifeh;Fatma Taher;Mohammed Ghazal;Neal Dunlap;Adel Elmaghraby;Robert Keynton;Ayman El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Lung cancer leads deaths caused by cancer for both men and women worldwide, that is why creating systems for early diagnosis with machine learning algorithms and nominal user intervention is of huge importance. In this manuscript, a new system for lung nodule diagnosis, using features extracted from one computed tomography (CT) scan, is presented. This system integrates global and local features t...Show More
A Machine Learning Approach for Grading Autism Severity Levels Using Task-based Functional MRI
Reem Haweel;Omar Dekhil;Ahmed Shalaby;Ali Mahmoud;Mohammed Ghazal;Robert Keynton;Gregory Barnes;Ayman El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Cited by: Papers (12)
Autism is a developmental disorder associated with difficulties in communication and social interaction. Autism diagnostic observation schedule (ADOS) is considered the gold standard in autism diagnosis, which estimates a score explaining the severity level for each individual. Currently, brain image modalities are being investigated for the development of objective technologies to diagnose Autism...Show More
A Deep Learning-Based Approach for Accurate Segmentation of Bladder Wall using MR Images
K. Hammouda;F. Khalifa;A. Soliman;M. Ghazal;M. Abou El-Ghar;A. Haddad;M. Elmogy;H. E. Darwish;R. Keynton;A. El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Cited by: Papers (15)
In this paper, a deep learning-based convolution neural network (CNN) is developed for accurate segmentation of the bladder wall using T2-weighted magnetic resonance imaging (T2W-MRI). Our framework utilizes a dual pathway, two-dimensional CNN for pathological bladder segmentation. Due to large bladder shape variability across subjects and the existence of pathology, a learnable adaptive shape pri...Show More
Autism Spectrum Disorder Diagnosis framework using Diffusion Tensor Imaging
Yaser ElNakieb;Ahmed Soliman;Ali Mahmoud;Omar Dekhil;Ahemd Shalaby;Mohammed Ghazal;Ashraf Khalil;Andrew Switala;Robert S. Keynton;Gregory N. Barnes;Ayman S. El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Cited by: Papers (8)
Autism is a complex neurological disorder which affects behavioral and communication skills. Numerous studies were presented suggesting abnormal development of neural networks in the brain in shape, functionality, and/or connectivity. While conventional diagnosis of autism is subjective and requires long time before confirmation, neuro-imaging techniques provide a promising alternative. This paper...Show More
Automatic Segmentation and Functional Assessment of the Left Ventricle using U-net Fully Convolutional Network
Hisham Abdeltawab;Fahmi Khalifa;Fatma Taher;Garth Beache;Tamer Mohamed;Adel Elmaghraby;Mohammed Ghazal;Robert Keynton;Ayman El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
A new method for the automatic segmentation and quantitative assessment of the left ventricle (LV) is proposed in this paper. The method is composed of two steps. First, a fully convolutional U-net is used for the segmentation of the epi- and endo-cardial boundaries of the LV from cine MR images. This step incorporates a novel loss function that accounts for the class imbalance problem caused by t...Show More
A Local/Regional Based CAD System for Early Diagnosis of Alzheimer's Disease Using sMRI Scans
Fatma El-Zahraa A. El-Gamal;Mohammed M. Elmogy;Ashraf Khalil;Mohammed Ghazal;Hassan Soliman;Ahmed Atwan;Robert Keynton;Gregory N. Barnes;Ayman S. El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Alzheimer's disease (AD) is one of the neurodegenerative diseases, an irreparable one, that targets the central nervous system and causes dementia. During its progression, the disease goes through a number of stages where the diagnosis of the disease at its early stage is highly recommended. Despite this recommendation, accomplishing this diagnosis task faces a number of obstacles including the va...Show More
An Accurate System for Prostate Cancer Localization from Diffusion-Weighted MRI
Islam R. Abdelmaksoud;Mohammed Ghazal;Ahmed Shalaby;Mohammed Elmogy;Ahmed Aboulfotouh;Mohamed Abou El-Ghar;Robert Keynton;Ayman El-Baz
2019 IEEE International Conference on Imaging Systems and Techniques (IST)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
This paper proposes a computer-aided diagnosis (CAD) system for localizing prostate cancer from diffusion-weighted magnetic resonance imaging (DW-MRI). This system uses DW-MRI data sets that were acquired at four b-values: 100, 200, 300, and 400 smm-2. The first step in the proposed system is prostate segmentation using a level set method. The evolution of this level set is guided not only by the ...Show More
A Novel Deep Learning Approach for Left Ventricle Automatic Segmentation in Cardiac Cine MR
Hisham Abdeltawab;Fahmi Khalifa;Fatma Taher;Garth Beache;Tamer Mohamed;Adel Elmaghraby;Mohammed Ghazal;Robert Keynton;Ayman El-Baz
2019 Fifth International Conference on Advances in Biomedical Engineering (ICABME)
Year: 2019 | Conference Paper |
Cited by: Papers (5)
Cardiac magnetic resonance imaging provides a way for heart's functional analysis. Through segmentation of the left ventricle from cardiac cine images, physiological parameters can be obtained. However, manual segmentation of the left ventricle requires significant time and effort. Therefore, automated segmentation of the left ventricle is the desired and practical alternative. This paper introduc...Show More
Functional Magnetic Resonance Imaging Based Framework for Autism Diagnosis
Reem Haweel;Omar Dekhil;Ahmed Shalaby;Ali Mahmoud;Mohammed Ghazal;Ashraf Khalil;Said Ghoniemy;Robert Keynton;Adel Elmaghraby;Gregory Barnes;Ayman El-Baz
2019 Fifth International Conference on Advances in Biomedical Engineering (ICABME)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
In this paper, a novel framework for global diagnosis of autism spectrum disorder (ASD) using task-based functional MRI data is presented. A speech fMRI experiment is held to obtain local features related to the functional activity of the brain. This study proposes both global diagnosis and local diagnosis by analyzing brain brainnetome atlas (BNT) which will lead to the first step of providing pe...Show More
A CNN-Based Framework for Bladder Wall Segmentation Using MRI
K. Hammouda;F. Khalifa;A. Soliman;M. Ghazal;M. Abou El-Ghar;A. Haddad;M. Elmogy;H. E. Darwish;A. Khalil;A. Elmaghraby;R. Keynton;A. El-Baz
2019 Fifth International Conference on Advances in Biomedical Engineering (ICABME)
Year: 2019 | Conference Paper |
Cited by: Papers (10)
Accurate segmentation of the bladder wall is of great importance for any computer-aided diagnostic system for bladder cancer (BC) detection and diagnosis. In this paper, a deep learning-based framework is developed for accurate segmentation of the bladder wall using T2-weighted magnetic resonance imaging (T2W-MRI). Our framework utilizes 3D convolution neural network (CNN) and incorporates context...Show More
Early Assessment of Renal Transplants Using BOLD-MRI: Promising Results
M. Shehata;A. Shalaby;M. Ghazal;M. Abou El-Ghar;M. A. Badawy;G. Beache;A. Dwyer;M. El-Melegy;G. Giridharan;R. Keynton;A. El-Baz
2019 IEEE International Conference on Image Processing (ICIP)
Year: 2019 | Conference Paper |
Cited by: Papers (5)
Non-invasive evaluation of renal transplant function is essential to minimize and manage acute renal rejection (AR). A computer-assisted diagnostic (CAD) system is developed to evaluate kidney function post-transplantation. The developed CAD system utilizes the amount of blood-oxygenation extracted from 3D (2D + time) blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) to estimate r...Show More
Detecting and Localizing Prostate Cancer from Diffusion-Weighted Magnetic Resonance Imaging
Islam Reda;Mohammed Ghazal;Ahmed Shalaby;Mohammed Elmogy;Ahmed Aboulfotouh;Mohamed Abou El-Ghar;Moumen El-Melegy;Ashraf Khalil;Robert Keynton;Ayman El-Baz
2019 IEEE International Conference on Image Processing (ICIP)
Year: 2019 | Conference Paper |
Cited by: Papers (3)
The purpose of this work is to develop a computer-aided diagnosis (CAD) system for detecting and localizing prostate cancer from diffusion-weighted magnetic resonance imaging (DWI) acquired at five distinct b-values. The first step in the proposed system depends on nonnegative matrix factorization (NMF) to fuse intensity features of prostate voxels, spatial features of neighboring voxels, and shap...Show More
Early Signs Detection of Diabetic Retinopathy Using Optical Coherence Tomography Angiography Scans Based on 3D Multi-Path Convolutional Neural Network
Nabila Eladawi;Mohammed Elmogy;Mohammed Ghazal;Luay Fraiwan;Ahmed Aboelfetouh;Alaa Riad;Harpal Sandhu;Robert Keynton;Ayman El-Baz
2019 IEEE International Conference on Image Processing (ICIP)
Year: 2019 | Conference Paper |
Cited by: Papers (8)
Diabetic Retinopathy (DR) is one of the leading causes of blindness in working age population worldwide. DR is caused by high blood sugar levels (diabetes), which damages retinal blood vessels and leads to vision loss. The diagnosis of DR requires manual measurements and visual assessment of the changes that happen in the retina, which is highly complex task. Thus, there is an unmet clinical need ...Show More
Early Signs Detection of Diabetic Retinopathy Using Optical Coherence Tomography Angiography Scans Based on 3D Multi-Path Convolutional Neural Network
Nabila Eladawi;Mohammed Elmogy;Mohammed Ghazal;Luay Fraiwan;Ahmed Aboelfetouh;Alaa Riad;Harpal Sandhu;Robert Keynton;Ayman El-Baz
Year: 2019 | Conference Paper |
A Novel CT-Based Descriptors for Precise Diagnosis of Pulmonary Nodules
Ahmed Shaffie;Ahmed Soliman;Hadil Abu Khalifeh;Fatma Taher;Mohammed Ghazal;Neal Dunlap;Adel Elmaghraby;Robert Keynton;Ayman El-Baz
2019 IEEE International Conference on Image Processing (ICIP)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Early diagnosis of pulmonary nodules is critical for lung cancer clinical management. In this paper, a novel framework for pulmonary nodule diagnosis, using descriptors extracted from single computed tomography (CT) scan, is introduced. This framework combines appearance and shape descriptors to give an indication of the nodule prior growth rate, which is the key point for diagnosis of lung nodule...Show More
Diabetic Retinopathy Early Detection Based on OCT and OCTA Feature Fusion
Nabila Eladawi;Ahmed ElTanboly;Mohammed Elmogy;Mohammed Ghazal;Luay Fraiwan;Ahmed Aboelfetouh;Alaa Riad;Robert Keynton;Magdi El-Azab;Shlomit Schaal;Ayman El-Baz
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
Diabetic retinopathy (DR) is one of the major causes of blindness worldwide. It is a diabetes complication that occurs after the damage of the blood vessels in the light-sensitive tissue in the retina. So, early detection of DR could reduce the severity of the disease and help ophthalmologists in treating and investigating it more efficiently. In this paper, we developed a computer-aided diagnosis...Show More
Detecting Prostate Cancer Using A CNN-Based System Without Segmentation
Islam Reda;Mohammed Ghazal;Ahmed Shalaby;Mohammed Elmogy;Ahmed Aboulfotouh;Mohamed Abou El-Ghar;Adel Elmaghraby;Robert Keynton;Ayman El-Baz
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
A computer-aided diagnosis (CAD) system for early detection of prostate cancer from diffusion-weighted magnetic resonance imaging (DWI) is proposed in this paper. The proposed system starts by defining a region of interest that includes the prostate across the different slices of the input DWI volume. Then, the apparent diffusion coefficient (ADC) of the defined ROI is calculated, normalized and r...Show More
Radiomic-Based Framework for Early Diagnosis of Lung Cancer
Ahmed Shaffie;Ahmed Soliman;Hadil Abu Khalifeh;Mohammed Ghazal;Fatma Taher;Adel Elmaghraby;Robert Keynton;Ayman El-Baz
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Year: 2019 | Conference Paper |
Cited by: Papers (13)
This paper proposes a new framework for pulmonary nodule diagnosis using radiomic features extracted from a single computed tomography (CT) scan. The proposed framework integrates appearance and shape features to get a precise diagnosis for the extracted lung nodules. The appearance features are modeled using 3D Histogram of Oriented Gradient (HOG) and higher-order Markov Gibbs random field (MGRF)...Show More
Computer-Aided Diagnostic System for Early Detection of Acute Renal Transplant Rejection Using Diffusion-Weighted MRI
Mohamed Shehata;Fahmi Khalifa;Ahmed Soliman;Mohammed Ghazal;Fatma Taher;Mohamed Abou El-Ghar;Amy C. Dwyer;Georgy Gimel’farb;Robert S. Keynton;Ayman El-Baz
Objective: Early diagnosis of acute renal transplant rejection (ARTR) is critical for accurate treatment. Although the current gold standard, diagnostic technique is renal biopsy, it is not preferred due to its invasiveness, long recovery time (1-2 weeks), and potential for complications, e.g., bleeding and/or infection. Methods: This paper presents a computer-aided diagnostic (CAD) system for ear...Show More
A Computer-Aided System for Prostate Cancer Diagnosis
Islam Reda;Mohammed Ghazal;Ahmed Shalaby;Mohammed Elmogy;Ahmed Aboulfotouh;Mohamed Abou El-Ghar;Adel Elmaghraby;Robert Keynton;Ayman El-Baz
2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
In this paper, a computer-aided diagnosis (CAD) system for early diagnosis of prostate cancer from diffusion-weighted magnetic resonance imaging (DWI) is proposed. The proposed system begins with defining a region of interest that contains the prostate across the various slices of the input volume. Then, the apparent diffusion coefficient (ADC) of the defined region is calculated, normalized and r...Show More
Diabetic Retinopathy Early Detection Based on OCT and OCTA Feature Fusion
Ahmed ElTanboly;Nabila Eladawi;Mohammed Elmogy;Mohammed Ghazal;Luay Fraiwan;A. Aboelfetouh;A. Riad;R. Keynton;M. El-Azab;S. Schaal;H. Sandhu;A. El-Baz
2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
Year: 2018 | Conference Paper |
Cited by: Papers (3)
Diabetic retinopathy (DR) is a leading cause of vision loss in adults between 20 and 74 years. It is one of the significant causes of blindness worldwide. It affects the blood vessels in the retina as a complication of diabetes. Early detection of DR could reduce the severity of the disease and help ophthalmologists in treating and investigating it more efficiently. In this paper, a computer-aided...Show More
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