R
Raad Mohiaddin
Researcher at National Institutes of Health
Publications - 43
Citations - 1083
Raad Mohiaddin is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Magnetic resonance imaging & Segmentation. The author has an hindex of 14, co-authored 43 publications receiving 652 citations. Previous affiliations of Raad Mohiaddin include Imperial College London.
Papers
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Journal ArticleDOI
Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge
Xiahai Zhuang,Lei Li,Christian Payer,Darko Štern,Martin Urschler,Mattias P. Heinrich,Julien Oster,Chunliang Wang,Örjan Smedby,Cheng Bian,Xin Yang,Pheng-Ann Heng,Aliasghar Mortazi,Ulas Bagci,Guanyu Yang,Chenchen Sun,Gaetan Galisot,Jean-Yves Ramel,Thierry Brouard,Qianqian Tong,Weixin Si,Xiangyun Liao,Guodong Zeng,Zenglin Shi,Guoyan Zheng,Chengjia Wang,Tom MacGillivray,David E. Newby,Kawal Rhode,Sebastien Ourselin,Raad Mohiaddin,Jennifer Keegan,David N. Firmin,Guang Yang +33 more
TL;DR: This work presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017.
Journal ArticleDOI
SCMR Position Paper (2020) on clinical indications for cardiovascular magnetic resonance.
Tim Leiner,Jan Bogaert,Jan Bogaert,Matthias G. Friedrich,Raad Mohiaddin,Vivek Muthurangu,Saul G. Myerson,Andrew J. Powell,Andrew J. Powell,Subha V. Raman,Dudley J. Pennell +10 more
TL;DR: This new Consensus Panel report brings those indications up to date for 2020 and includes the very substantial increase in scanning techniques, clinical applicability and adoption of CMR worldwide.
Book ChapterDOI
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction
Maximilian Seitzer,Guang Yang,Jo Schlemper,Ozan Oktay,Tobias Würfl,Vincent Christlein,Tom Wong,Raad Mohiaddin,David N. Firmin,Jennifer Keegan,Daniel Rueckert,Andreas Maier +11 more
TL;DR: In this paper, a visual refinement component is learned on top of an MSE loss-based reconstruction network and a semantic interpretability score is introduced to measure the visibility of the region of interest in both ground truth and reconstructed images.
Journal ArticleDOI
Simultaneous left atrium anatomy and scar segmentations via deep learning in multiview information with attention.
Guang Yang,Jun Chen,Zhifan Gao,Shuo Li,Hao Ni,Hao Ni,Elsa D. Angelini,Tom Wong,Raad Mohiaddin,Eva Nyktari,Ricardo Wage,Lei Xu,Yanping Zhang,Xiuquan Du,Heye Zhang,David N. Firmin,Jennifer Keegan +16 more
TL;DR: A joint segmentation method based on multiview two-task (MVTT) recursive attention model working directly on 3D LGE CMR images to segment the LA (and proximal pulmonary veins) and to delineate the scar on the same dataset is proposed.
Journal ArticleDOI
Atrial scar quantification via multi-scale CNN in the graph-cuts framework.
Lei Li,Fuping Wu,Guang Yang,Lingchao Xu,Tom Wong,Raad Mohiaddin,David N. Firmin,Jennifer Keegan,Xiahai Zhuang +8 more
TL;DR: In this article, the potentials of the graph are learned on a surface mesh of the left atrium (LA) using a multi-scale convolutional neural network (MS-CNN).