A. Fahmy

发表

Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.

Reza Nezafat, Warren J Manning, Ahmed S Fahmy, 2019, Radiology.

Dynamic and quantitative analysis of choroidal neovascularization by fluorescein angiography.

P. Campochiaro, I. Zimmer-Galler, J. Cedarbaum, 2006, Investigative ophthalmology & visual science.

Segmentation of Choroidal Neovascularization lesions in fluorescein angiograms using parametric modeling of the intensity variation

Ahmed S. Fahmy, Walid M. Abdelmoula, Ahmed Essam Mahfouz, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Greedy framework for optical flow tracking of myocardium contours

Ayman M. Khalifa, Ahmed S. Fahmy, Ahmed O. Al-Agamy, 2014, IET Image Process..

6 Continuum Mechanics and Mechanical Cardiac Models

El-Sayed H. Ibrahim, A. Fahmy, 2017 .

Automated analysis of cardiovascular magnetic resonance myocardial native T1 mapping images using fully convolutional neural networks

Reza Nezafat, Ahmed S. Fahmy, Maryam Nezafat, 2019, Journal of Cardiovascular Magnetic Resonance.

Prediction of diabetic foot ulceration using spatial and temporal dynamic plantar pressure

Fady S. Botros, M. Taher, A. Fahmy, 2016, 2016 8th Cairo International Biomedical Engineering Conference (CIBEC).

Additional file 3: of Automated analysis of cardiovascular magnetic resonance myocardial native T1 mapping images using fully convolutional neural networks

Reza Nezafat, Ahmed S. Fahmy, Maryam Nezafat, 2019 .

An Explainable Machine Learning Approach Reveals Prognostic Significance of Right Ventricular Dysfunction in Nonischemic Cardiomyopathy.

L. Ngo, W. Manning, R. Kwong, 2022, JACC. Cardiovascular imaging.

Black blood myocardial T2 mapping

Jue Zhang, Chengyan Wang, Xiaoying Wang, 2018, Magnetic resonance in medicine.

Improved estimation of the cardiac global function using combined long and short axis MRI images of the heart

A. Fahmy, Hossam El-Rewaidy, 2016, Biomedical engineering online.

Combining long and short axis myocardial contours for accurate reconstruction of the left ventricular surface

A. Fahmy, Hossam El-Rewaidy, A. Khalifa, 2014, 2nd Middle East Conference on Biomedical Engineering.

Strain Encoding (SENC)

El-Sayed H. Ibrahim, A. Fahmy, 2017 .

Radiomics and deep learning for myocardial scar screening in hypertrophic cardiomyopathy

R. Nezafat, M. Maron, A. Fahmy, 2022, Journal of Cardiovascular Magnetic Resonance.

Non‐contrast myocardial infarct scar assessment using a hybrid native T1 and magnetization transfer imaging sequence at 1.5T

Yanjie Zhu, R. Nezafat, A. Fahmy, 2018, Magnetic resonance in medicine.

Segmentation of the Right Ventricle in MR images using dual active shape model in the Bookstein coordinates

Ahmed S. Fahmy, Hossam El-Rewaidy, A. Fahmy, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Automatic localization of the left ventricle in cardiac MRI images using deep learning

Inas A. Yassine, Ahmed S. Fahmy, Omar Emad, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Cardiovascular magnetic resonance feature tracking strain analysis for discrimination between hypertensive heart disease and hypertrophic cardiomyopathy

W. Manning, R. Nezafat, A. Fahmy, 2019, PloS one.

The Impact of a Rigorous Quality Program on 3D Echocardiography Data Quality in an International Multisite Randomized Trial

Bjoern H Menze, R. Nezafat, M. Maron, 2018 .

Machine Learning for Predicting Heart Failure Progression in Hypertrophic Cardiomyopathy

W. Manning, R. Nezafat, M. Maron, 2021, Frontiers in Cardiovascular Medicine.

Multi‐domain convolutional neural network (MD‐CNN) for radial reconstruction of dynamic cardiac MRI

Reza Nezafat, Ibolya Csecs, Bjoern H Menze, 2020, Magnetic resonance in medicine.

Automated Myocardial T2 and Extracellular Volume Quantification in Cardiac MRI Using Transfer Learning-based Myocardium Segmentation.

Reza Nezafat, Yanjie Zhu, Chong Duan, 2020, Radiology. Artificial intelligence.

Changes in Myocardial Native T1 and T2 After Exercise Stress: A Noncontrast CMR Pilot Study.

L. Ngo, W. Manning, R. Nezafat, 2020, JACC. Cardiovascular imaging.

Gray blood late gadolinium enhancement cardiovascular magnetic resonance for improved detection of myocardial scar

L. Ngo, W. Manning, R. Nezafat, 2018, Journal of Cardiovascular Magnetic Resonance.

Cardiac MRI view classification using autoencoder

Inas A. Yassine, Ahmed S. Fahmy, Mahmoud S. Shaker, 2014, 2014 Cairo International Biomedical Engineering Conference (CIBEC).

Automated Cardiac MR Scar Quantification in Hypertrophic Cardiomyopathy Using Deep Convolutional Neural Networks.

Reza Nezafat, Bjoern H Menze, Bjoern Menze, 2018, JACC. Cardiovascular imaging.

Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T 1 mapping images

Maryam Nezafat, Ahmed S Fahmy, Hossam El-Rewaidy, 2020, Physics in medicine and biology.

Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach

W. Manning, R. Nezafat, M. Maron, 2021, Journal of magnetic resonance imaging : JMRI.

Multiple two-dimensional active shape model framework for right ventricular segmentation.

A. Fahmy, Hossam El-Rewaidy, A. Khalifa, 2021, Magnetic resonance imaging.

Segmentation of the right ventricle in MRI images using a dual active shape model

El-Sayed H. Ibrahim, Ahmed S. Fahmy, Hossam El-Rewaidy, 2016, IET Image Process..

Fast Localization of the Optic Disc Using Projection of Image Features

Ahmed S. Fahmy, Ahmed Essam Mahfouz, A. Fahmy, 2010, IEEE Transactions on Image Processing.

A collaborative resource to build consensus for automated left ventricular segmentation of cardiac MR images

Nicholas Ayache, Simon K. Warfield, Alistair A. Young, 2014, Medical Image Anal..

Detecting liver fibrosis using a machine learning‐based approach to the quantification of the heart‐induced deformation in tagged MR images

T. Basha, A. Fahmy, A. Khalifa, 2019, NMR in biomedicine.

Strain‐encoded MRI to evaluate normal left ventricular function and timing of contraction at 3.0 Tesla

Sebastian Kelle, Eckart Fleck, Axel Bornstedt, 2009, Journal of magnetic resonance imaging : JMRI.

Regional right ventricular function and timing of contraction in healthy volunteers evaluated by strain‐encoded MRI

Eckart Fleck, Ernst Wellnhofer, Ashraf Hamdan, 2008, Journal of magnetic resonance imaging : JMRI.

Real‐time MR imaging of myocardial regional function using strain‐encoding (SENC) with tissue through‐plane motion tracking

Matthias Stuber, Nael F Osman, Khaled Z. Abd-Elmoniem, 2007, Journal of magnetic resonance imaging : JMRI.

Noncontrast Cardiac Magnetic Resonance Imaging Predictors of Heart Failure Hospitalization in Heart Failure With Preserved Ejection Fraction

L. Ngo, R. Nezafat, A. Fahmy, 2021, Journal of magnetic resonance imaging : JMRI.

Convolutional neural networks for deep feature learning in retinal vessel segmentation

Inas A. Yassine, Ahmed S. Fahmy, Aya F. Khalaf, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Segmentation of Choroidal Neovascularization in Fundus Fluorescein Angiograms

Ahmed S. Fahmy, Walid M. Abdelmoula, Syed Mahmoud Shah, 2013, IEEE Transactions on Biomedical Engineering.

Additional file 1: of Automated analysis of cardiovascular magnetic resonance myocardial native T1 mapping images using fully convolutional neural networks

Reza Nezafat, Ahmed S. Fahmy, Maryam Nezafat, 2019 .

Content based image retrieval of diabetic macular edema images

Ahmed S. Fahmy, Ahmed M. Ghanem, Aya M. Naguib, 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

Spectrally-Presaturated Modulation (SPM): An efficient fat suppression technique for STEAM-based cardiac imaging sequences.

El-Sayed H Ibrahim, Nael F Osman, El-Sayed H. Ibrahim, 2017, Magnetic resonance imaging.

Artifact-free black-blood cine cardiac imaging in a single breath-hold.

Nael F Osman, Li Pan, Ahmed S Fahmy, 2006, Magnetic resonance imaging.

Computer-aided analysis of fluorescein angiograms using colour leakage maps

Mohamed Ibrahim, Ahmed S. Fahmy, Eman Magdy, 2015, IET Image Process..

Radiomics of Late Gadolinium Enhancement Reveals Prognostic Value of Myocardial Scar Heterogeneity in Hypertrophic Cardiomyopathy.

W. Manning, R. Nezafat, M. Maron, 2023, JACC. Cardiovascular imaging.

Detection of Cardiac Function Abnormality from MRI Images Using Normalized Wall Thickness Temporal Patterns

El-Sayed H. Ibrahim, Ahmed S. Fahmy, Mai Wael, 2016, Int. J. Biomed. Imaging.

The Impact of a Rigorous Quality Program on 3D Echocardiography Data Quality in an International Multisite Randomized Trial.

Bjoern H Menze, E. Yow, H. Barnhart, 2018, JACC. Cardiovascular imaging.

Quantitative assessment of Diabetic Macular Edema using fluorescein leakage maps

Mohamed Ibrahim, Ahmed S. Fahmy, Eman Magdy, 2012, 2012 19th IEEE International Conference on Image Processing.

Nonrigid active shape model–based registration framework for motion correction of cardiac T1 mapping

Reza Nezafat, Ahmed S. Fahmy, Maryam Nezafat, 2018, Magnetic resonance in medicine.

Maximum likelihood estimator for signal intensity in STEAM-based MR imaging techniques

Nael F. Osman, Ahmed S. Fahmy, Heba A. Shalaby, 2011, 2011 IEEE 7th International Conference on Intelligent Computer Communication and Processing.

Segmentation of strain-encoded magnetic resonance images using graph-cuts

Ahmed S. Fahmy, Ahmed O. Al-Agamy, A. Fahmy, 2011, 2011 IEEE 7th International Conference on Intelligent Computer Communication and Processing.

Inherent fat cancellation in complementary spatial modulation of magnetization

N. Osman, T. Basha, A. Fahmy, 2009, Magnetic resonance in medicine.

Performance Evaluation of Cardiac MRI Image Denoising Techniques

N. Osman, A. Fahmy, A. Motaal, 2008, 2008 Cairo International Biomedical Engineering Conference.

Cardiac MRI Steam Images Denoising using Bayes Classifier

N. Osman, A. Fahmy, A. Motaal, 2008, 2008 Cairo International Biomedical Engineering Conference.

Background noise removal in cardiac magnetic resonance images using bayes classifier

Ahmed S. Fahmy, A. Fahmy, 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Two clustering techniques of myocardium using C-SENC images: A comparison with multi-stage clustering

Y.M. Kadah, Y. M. Kadah, N.F. Osman, 2007, 2007 International Conference on Computer Engineering & Systems.

An integrated system for real-time detection of stiff masses with a single compression

Axel Krieger, Nael F. Osman, Ahmed S. Fahmy, 2006, IEEE Transactions on Biomedical Engineering.

Correction of through‐plane deformation artifacts in stimulated echo acquisition mode cardiac imaging

Matthias Stuber, Nael F Osman, Ahmed S Fahmy, 2006, Magnetic resonance in medicine.

Quantification of soft tissue deformations using strain-encoded magnetic resonance imaging

Nael F. Osman, Ahmed S. Fahmy, N. Osman, 2004, SPIE Medical Imaging.

Determining the through-plane resolution of strain-encoded MRI

Nael F. Osman, Ahmed S. Fahmy, N. Osman, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

Error analysis of fundus image registration using quadratic model transfformation

Ahmed S. Fahmy, Safaa M. Eldeeb, A. Fahmy, 2014, 2014 Cairo International Biomedical Engineering Conference (CIBEC).

Scanner‐Independent MyoMapNet for Accelerated Cardiac MRI T1 Mapping Across Vendors and Field Strengths

Jiwon Kim, R. Judd, J. Weinsaft, 2023, Journal of magnetic resonance imaging : JMRI.