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Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation.

W. Bai, O. Oktay, M. Sinclair, H. Suzuki, M. Rajchl, G. Tarroni, B. Glocker, A. King, P. Matthews, and D. Rueckert. MICCAI (2), volume 10434 of Lecture Notes in Computer Science, page 253-260. Springer, (2017)

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

Other publications of authors with the same name

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)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)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: 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)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)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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Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation.

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

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Disambiguation of "Oktay, Ozan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation.

Please choose a person to relate this publication to

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

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Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation.