Mahmoud Mostapha
from Princeton, NJ
Mahmoud Mostapha Phones & Addresses
- Princeton, NJ
- Chapel Hill, NC
- Louisville, KY
Work
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Company:Siemens healthcareApr 2020
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Position:Senior ai scientist
Education
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Degree:Doctorates, Doctor of Philosophy
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School / High School:University of North Carolina at Chapel Hill2012 to 2016
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Specialities:Computer Science, Philosophy
Skills
Matlab • Microsoft Word • Programming • Computer Vision • C++ • Latex • Digital Image Processing • Medical Imaging • Powerpoint • Microsoft Office • Research • Teaching • Microsoft Excel • Customer Service • Digital Signal Processing • Pattern Recognition • Software Engineering • University Teaching • Linux • Java • Assembly Language • Vhdl • Simulink • Robotics • Wireless Sensor Networks • Medical Image Analysis • Neuroscience • Vtk • Itk • Python • Computational Physics • C • Machine Learning • Computer Science • Image Processing • Neuroimaging • Deep Learning • Theano • Tensorflow • Keras • Scientific Computing • Applied Mathematics • Computational Mathematics • Statistics • Optimization • Science • Algorithms • Mathematical Modeling
Languages
Arabic • English
Interests
Travelling • Music • Playing Football
Industries
Computer Software
Resumes
Senior Ai Scientist
view sourceLocation:
2800 south Floyd St, Louisville, KY 40209
Industry:
Computer Software
Work:
Siemens Healthcare
Senior Ai Scientist
University of North Carolina at Chapel Hill Aug 2018 - Jan 2019
Graduate Student Instructor
University of North Carolina at Chapel Hill Aug 2015 - Dec 2015
Graduate Research Assistant
University of Louisville Aug 2014 - Aug 2015
Graduate Fellow
University of Louisville Aug 2015 - Jul 2014
Graduate Research Assistant
Senior Ai Scientist
University of North Carolina at Chapel Hill Aug 2018 - Jan 2019
Graduate Student Instructor
University of North Carolina at Chapel Hill Aug 2015 - Dec 2015
Graduate Research Assistant
University of Louisville Aug 2014 - Aug 2015
Graduate Fellow
University of Louisville Aug 2015 - Jul 2014
Graduate Research Assistant
Education:
University of North Carolina at Chapel Hill 2012 - 2016
Doctorates, Doctor of Philosophy, Computer Science, Philosophy University of Louisville 2014 - 2015
Doctorates, Doctor of Philosophy, Computer Engineering, Philosophy University of Louisville 2013 - 2014
Masters, Computer Engineering Mansoura University 2004 - 2009
Bachelors, Electronics, Engineering, Communications
Doctorates, Doctor of Philosophy, Computer Science, Philosophy University of Louisville 2014 - 2015
Doctorates, Doctor of Philosophy, Computer Engineering, Philosophy University of Louisville 2013 - 2014
Masters, Computer Engineering Mansoura University 2004 - 2009
Bachelors, Electronics, Engineering, Communications
Skills:
Matlab
Microsoft Word
Programming
Computer Vision
C++
Latex
Digital Image Processing
Medical Imaging
Powerpoint
Microsoft Office
Research
Teaching
Microsoft Excel
Customer Service
Digital Signal Processing
Pattern Recognition
Software Engineering
University Teaching
Linux
Java
Assembly Language
Vhdl
Simulink
Robotics
Wireless Sensor Networks
Medical Image Analysis
Neuroscience
Vtk
Itk
Python
Computational Physics
C
Machine Learning
Computer Science
Image Processing
Neuroimaging
Deep Learning
Theano
Tensorflow
Keras
Scientific Computing
Applied Mathematics
Computational Mathematics
Statistics
Optimization
Science
Algorithms
Mathematical Modeling
Microsoft Word
Programming
Computer Vision
C++
Latex
Digital Image Processing
Medical Imaging
Powerpoint
Microsoft Office
Research
Teaching
Microsoft Excel
Customer Service
Digital Signal Processing
Pattern Recognition
Software Engineering
University Teaching
Linux
Java
Assembly Language
Vhdl
Simulink
Robotics
Wireless Sensor Networks
Medical Image Analysis
Neuroscience
Vtk
Itk
Python
Computational Physics
C
Machine Learning
Computer Science
Image Processing
Neuroimaging
Deep Learning
Theano
Tensorflow
Keras
Scientific Computing
Applied Mathematics
Computational Mathematics
Statistics
Optimization
Science
Algorithms
Mathematical Modeling
Interests:
Travelling
Music
Playing Football
Music
Playing Football
Languages:
Arabic
English
English
Us Patents
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Image Correction Using An Invertable Network
view source -
US Patent:20230079353, Mar 16, 2023
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Filed:Sep 14, 2021
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Appl. No.:17/474363
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Inventors:- Erlangen, DE
Mariappan S. Nadar - Plainsboro NJ, US
Simon Arberet - Princeton NJ, US
Mahmoud Mostapha - Princeton NJ, US -
International Classification:G06T 7/00
G06N 20/00
G06T 5/00 -
Abstract:For correction of an image from an imaging system, an inverse solution uses an imaging prior as a regularizer and a physics model of the imaging system. An invertible network is used as the deep-learnt generative model in the regularizer of the inverse solution with the physics model of the degradation behavior of the imaging system. The prior model based on the invertible network provides a closed-form expression of the prior probability, resulting in a more versatile or accurate probability prediction.
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Deep Learning-Based Realtime Reconstruction
view source -
US Patent:20230084413, Mar 16, 2023
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Filed:Sep 13, 2021
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Appl. No.:17/473229
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Inventors:- Erlangen, DE
Marcel Dominik Nickel - Herzogenaurach, DE
Simon Arberet - Princeton NJ, US
Boris Mailhe - Plainsboro NJ, US
Mahmoud Mostapha - Princeton NJ, US -
International Classification:G06T 11/00
G16H 30/20
G06N 3/08 -
Abstract:For reconstruction, a machine-learned model is adapted to allow for reconstruction based on the repetitions available in some scanning. The reconstruction for one or more subsets is performed during the scanning. The machine-learned model is trained to reconstruction separately or independently for each repetition or to use information from previous repetitions without requiring waiting for completion of scanning. The reconstructed image may be displayed much more rapidly after completion of the acquisition since the reconstruction begins during the reconstruction.
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Aggregation Based On Deep Set Learning In Magnetic Resonance Reconstruction
view source -
US Patent:20230085254, Mar 16, 2023
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Filed:Sep 13, 2021
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Appl. No.:17/473206
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Inventors:- Erlangen, DE
Boris Mailhe - Plainsboro NJ, US
Thomas Benkert - Neunkirchen am Brand, DE
Marcel Dominik Nickel - Herzogenaurach, DE
Mahmoud Mostapha - Princeton NJ, US
Mariappan S. Nadar - Plainsboro NJ, US -
International Classification:G06T 11/00
G16H 30/20
G06N 3/08 -
Abstract:For reconstruction in medical imaging using a scan protocol with repetition, a machine learning model is trained for reconstruction of an image for each repetition. Rather than using a loss for that repetition in training, the loss based on an aggregation of images reconstructed from multiple repetitions is used to train the machine learning model. This loss for reconstruction of one repetition based on aggregation of reconstructions for multiple repetitions is based on deep set-based deep learning. The resulting machine-learned model may better reconstruct an image from a given repetition and/or a combined image from multiple repetitions than a model learned from a loss per repetition.
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Mahmoud Mostapha
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Mahmoud Mostapha
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Mahmoud Mostapha
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Mahmoud Mostapha
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Mahmoud Mostapha
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Mostapha Mahmoud
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