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Jo Schlemper
Jo Schlemper
Hyperfine
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Title
Cited by
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
51222018
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
13572019
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
12082017
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
5562018
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
3782017
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
2002019
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
1602018
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
1272018
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
1142018
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
902020
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
882019
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
792020
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
662021
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
622018
Multi-coil magnetic resonance imaging using deep learning
J Schlemper, SSM Salehi, M Sofka
US Patent US 2020/0294287 A1, 2020
572020
& Rueckert, D.(2018). Attention u-net: Learning where to look for the pancreas
O Oktay, J Schlemper, LL Folgoc, M Lee, M Heinrich, K Misawa
arXiv preprint arXiv:1804.03999, 1804
521804
Attention u-net: Learning where to look for the pancreas
O Ozan, S Jo, LF Loic, L Matthew, H Mattias, M Kazunari, M Kensaku, ...
arXiv preprint arXiv:1804.03999, 2018
502018
Weakly supervised estimation of shadow confidence maps in fetal ultrasound imaging
Q Meng, M Sinclair, V Zimmer, B Hou, M Rajchl, N Toussaint, O Oktay, ...
IEEE transactions on medical imaging 38 (12), 2755-2767, 2019
492019
Deep learning techniques for alignment of magnetic resonance images
J Schlemper, SSM Salehi, M Sofka
US Patent US 2020/0294282 A1, 2020
482020
Self ensembling techniques for generating magnetic resonance images from spatial frequency data
J Schlemper, SSM Salehi, M Sofka
US Patent US2020/0294229 A1, 2020
482020
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