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Jo Schlemper
Jo Schlemper
Hyperfine
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Cited by
Year
Attention u-net: Learning where to look for the pancreas.
O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ...
arXiv preprint arXiv:1804.03999, 2018
67732018
Attention gated networks: Learning to leverage salient regions in medical images
J Schlemper, O Oktay, M Schaap, M Heinrich, B Kainz, B Glocker, ...
Medical image analysis 53, 197-207, 2019
16452019
A deep cascade of convolutional neural networks for dynamic MR image reconstruction
J Schlemper, J Caballero, JV Hajnal, AN Price, D Rueckert
IEEE transactions on Medical Imaging 37 (2), 491-503, 2017
13762017
Convolutional recurrent neural networks for dynamic MR image reconstruction
C Qin, J Schlemper, J Caballero, AN Price, JV Hajnal, D Rueckert
IEEE transactions on medical imaging 38 (1), 280-290, 2018
6642018
A deep cascade of convolutional neural networks for MR image reconstruction
J Schlemper, J Caballero, JV Hajnal, A Price, D Rueckert
Information Processing in Medical Imaging: 25th International Conference …, 2017
4302017
Attention u-net: Learning where to look for the pancreas. arXiv
O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ...
arXiv preprint arXiv:1804.03999 10, 2018
4082018
Attention u-net: learning where to look for the pancreas (2018)
O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa, K Mori, ...
arXiv preprint arXiv:1804.03999, 1804
2441804
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach
J Duan, G Bello, J Schlemper, W Bai, TJW Dawes, C Biffi, A de Marvao, ...
IEEE transactions on medical imaging 38 (9), 2151-2164, 2019
2212019
Joint learning of motion estimation and segmentation for cardiac MR image sequences
C Qin, W Bai, J Schlemper, SE Petersen, SK Piechnik, S Neubauer, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
1892018
Adversarial and perceptual refinement for compressed sensing MRI reconstruction
M Seitzer, G Yang, J Schlemper, O Oktay, T Würfl, V Christlein, T Wong, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
1352018
Attention-gated networks for improving ultrasound scan plane detection
J Schlemper, O Oktay, L Chen, J Matthew, C Knight, B Kainz, B Glocker, ...
arXiv preprint arXiv:1804.05338, 2018
1252018
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
J Duan, J Schlemper, C Qin, C Ouyang, W Bai, C Biffi, G Bello, B Statton, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
1042019
Systematic evaluation of iterative deep neural networks for fast parallel MRI reconstruction with sensitivity‐weighted coil combination
K Hammernik, J Schlemper, C Qin, J Duan, RM Summers, D Rueckert
Magnetic Resonance in Medicine 86 (4), 1859-1872, 2021
942021
Deep learning techniques for magnetic resonance image reconstruction
J Schlemper, SSM Salehi, M Sofka, P Kundu, Z Wang, C Lazarus, ...
US Patent US2020/0034998 A1, 2020
932020
Unsupervised multi-modal style transfer for cardiac MR segmentation
C Chen, C Ouyang, G Tarroni, J Schlemper, H Qiu, W Bai, D Rueckert
Statistical Atlases and Computational Models of the Heart. Multi-Sequence …, 2020
812020
Stochastic deep compressive sensing for the reconstruction of diffusion tensor cardiac MRI
J Schlemper, G Yang, P Ferreira, A Scott, LA McGill, Z Khalique, ...
International conference on medical image computing and computer-assisted …, 2018
642018
Attention u-net: Learning where to look for the pancreas
O Ozan, S Jo, F Loic, L Matthew, H Mattias, M Kazunari, M Kensaku, ...
arXiv preprint arXiv:1804.03999, 2018
632018
Multi-coil magnetic resonance imaging using deep learning
J Schlemper, SSM Salehi, M Sofka
US Patent US 2020/0294287 A1, 2020
622020
DSFormer: A dual-domain self-supervised transformer for accelerated multi-contrast MRI reconstruction
B Zhou, N Dey, J Schlemper, SSM Salehi, C Liu, JS Duncan, M Sofka
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2023
542023
Self ensembling techniques for generating magnetic resonance images from spatial frequency data
J Schlemper, SSM Salehi, M Sofka
US Patent US2020/0294229 A1, 2020
532020
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