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Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning.

J. Schlemper, O. Oktay, W. Bai, D. Castro, J. Duan, C. Qin, J. Hajnal, and D. Rueckert. MICCAI (1), volume 11070 of Lecture Notes in Computer Science, page 259-267. Springer, (2018)

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Prof. Dr. -Ing. Oktay Tabasaran University of Stuttgart

Other publications of authors with the same name

Image-and-Spatial Transformer Networks for Structure-Guided Image Registration.M. Lee, O. Oktay, A. Schuh, M. Schaap, and B. Glocker. CoRR, (2019)Attention-Gated Networks for Improving Ultrasound Scan Plane Detection.J. Schlemper, O. Oktay, L. Chen, J. Matthew, C. Knight, B. Kainz, B. Glocker, and D. Rueckert. CoRR, (2018)DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks.M. Rajchl, M. Lee, O. Oktay, K. Kamnitsas, J. Passerat-Palmbach, W. Bai, B. Kainz, and D. Rueckert. CoRR, (2016)Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images.J. Schlemper, O. Oktay, M. Schaap, M. Heinrich, B. Kainz, B. Glocker, and D. Rueckert. CoRR, (2018)Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation.O. Oktay, E. Ferrante, K. Kamnitsas, M. Heinrich, W. Bai, J. Caballero, S. Cook, A. de Marvao, T. Dawes, D. O'Regan and 3 other author(s). IEEE Trans. Med. Imaging, 37 (2): 384-395 (2018)Learning-Based Quality Control for Cardiac MR Images.G. Tarroni, O. Oktay, W. Bai, A. Schuh, H. Suzuki, J. Passerat-Palmbach, A. de Marvao, D. O'Regan, S. Cook, B. Glocker and 2 other author(s). IEEE Trans. Med. Imaging, 38 (5): 1127-1138 (2019)Learning a Global Descriptor of Cardiac Motion from a Large Cohort of 1000+ Normal Subjects.W. Bai, D. Peressutti, O. Oktay, W. Shi, D. O'Regan, A. King, and D. Rueckert. FIMH, volume 9126 of Lecture Notes in Computer Science, page 3-11. Springer, (2015)AutoDVT: Joint Real-Time Classification for Vein Compressibility Analysis in Deep Vein Thrombosis Ultrasound Diagnostics.R. Tanno, A. Makropoulos, S. Arslan, O. Oktay, S. Mischkewitz, F. Al-Noor, J. Oppenheimer, R. Mandegaran, B. Kainz, and M. Heinrich. MICCAI (2), volume 11071 of Lecture Notes in Computer Science, page 905-912. Springer, (2018)Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling.C. Biffi, O. Oktay, G. Tarroni, W. Bai, A. de Marvao, G. Doumou, M. Rajchl, R. Bedair, S. Prasad, S. Cook and 2 other author(s). MICCAI (2), volume 11071 of Lecture Notes in Computer Science, page 464-471. Springer, (2018)Real-Time Prediction of Segmentation Quality.R. Robinson, O. Oktay, W. Bai, V. Valindria, M. Sanghvi, N. Aung, J. Paiva, F. Zemrak, K. Fung, E. Lukaschuk and 10 other author(s). MICCAI (4), volume 11073 of Lecture Notes in Computer Science, page 578-585. Springer, (2018)

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Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning.

Please choose a person to relate this publication to

Prof. Dr. -Ing. Oktay Tabasaran University of Stuttgart

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning.

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Prof. Dr. -Ing. Oktay Tabasaran University of Stuttgart

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Disambiguation

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Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning.