Follow
Aliasghar Mortazi
Aliasghar Mortazi
Medical Image Processing Group(MIPG), Upenn
Verified email at uphs.upenn.edu - Homepage
Title
Cited by
Cited by
Year
Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge
X Zhuang, L Li, C Payer, D Štern, M Urschler, MP Heinrich, J Oster, ...
Medical image analysis 58, 101537, 2019
2492019
Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks
JR Burt, N Torosdagli, N Khosravan, H RaviPrakash, A Mortazi, ...
The British journal of radiology 91 (1089), 20170545, 2018
1682018
CardiacNET: Segmentation of Left Atrium and Proximal Pulmonary Veins from MRI Using Multi-view CNN
A Mortazi, R Karim, K Rhode, J Burt, U Bagci
Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 …, 2017
1272017
Automatically designing CNN architectures for medical image segmentation
A Mortazi, U Bagci
Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018 …, 2018
952018
Multi-planar deep segmentation networks for cardiac substructures from MRI and CT
A Mortazi, J Burt, U Bagci
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018
802018
The international workshop on osteoarthritis imaging knee MRI segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset
AD Desai, F Caliva, C Iriondo, A Mortazi, S Jambawalikar, U Bagci, ...
Radiology: Artificial Intelligence 3 (3), e200078, 2021
502021
Pan: Projective adversarial network for medical image segmentation
N Khosravan, A Mortazi, M Wallace, U Bagci
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
402019
Weakly supervised segmentation by a deep geodesic prior
A Mortazi, N Khosravan, DA Torigian, S Kurugol, U Bagci
International Workshop on Machine Learning in Medical Imaging, 238-246, 2019
72019
A multi-institute automated segmentation evaluation on a standard dataset: Findings from the international workshop on osteoarthritis imaging segmentation challenge
A Desai, F Caliva, C Iriondo, N Khosravan, A Mortazi, S Jambawalikar, ...
Osteoarthritis and Cartilage 28, S304-S305, 2020
42020
A post-acquisition standardization method for positron emission tomography images
A Mortazi, JK Udupa, Y Tong, DA Torigian
Medical Imaging 2020: Computer-Aided Diagnosis 11314, 907-912, 2020
32020
Selecting the best optimizers for deep learning–based medical image segmentation
A Mortazi, V Cicek, E Keles, U Bagci
Frontiers in Radiology 3, 2023
22023
Optimization Algorithms for Deep Learning Based Medical Image Segmentations
A Mortazi
22019
Using embodiment theory to train a set of actuators with different expertise to accomplish a duty: An application to train a quadruped robot for walking
A Mortazi, SB Shouraki
2015 23rd Iranian Conference on Electrical Engineering, 589-594, 2015
12015
Post-acquisition Standardization of Positron Emission Tomography Images
A Mortazi, JK Udupa, D Odhner, Y Tong, DA Torigian
Research Square, 2023
2023
Standardization Of Positron Emission Tomography Based Images
JK Udupa, A Mortazi, Y Tong, DA Torigian, D Odhner
US Patent App. 17/175,655, 2021
2021
Cardiac Image Analysis with Deep Learning Methods
A Mortazi, G Papadakis, U Teomete, U Bagci
Annual Meeting of the Radiological Society of North America, 2018
2018
Deep Learning for Cardiac MRI: Automatically Segmenting Left Atrium and Proximal Veins with Human Level Performance
A Mortazi, J Burt, U Bagci
Annual Meeting of the Radiological Society of North America, 2017
2017
Deep Learning Applications in Radiology: Recent Developments, Challenges and Potential Solutions
S Hussein, A Mortazi, H Raviprakash, JR Burtⱡ, U Bagci
Annual Meeting of the Radiological Society of North America, 2017
2017
A Report on the International Workshop on Osteoarthritis Imaging Segmentation Challenge: A Multi-Institute Evaluation on a Standard Dataset
AD Desai, F Caliva, C Iriondo, N Khosravan, A Mortazi, S Jambawalikar, ...
The system can't perform the operation now. Try again later.
Articles 1–19