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Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge.

A. Suinesiaputra, P. Ablin, X. Albà, M. Alessandrini, J. Allen, W. Bai, S. Çimen, P. Claes, B. Cowan, J. D'hooge, N. Duchateau, J. Ehrhardt, A. Frangi, A. Gooya, V. Grau, K. Lekadir, A. Lu, A. Mukhopadhyay, I. Öksüz, N. Parajuli, X. Pennec, M. Pereañez, C. Pinto, P. Piras, M. Rohé, D. Rueckert, D. Säring, M. Sermesant, K. Siddiqi, M. Tabassian, L. Teresi, S. Tsaftaris, M. Wilms, A. Young, X. Zhang, and P. Medrano-Gracia. IEEE J. Biomedical and Health Informatics, 22 (2): 503-515 (2018)

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Unsupervised Myocardial Segmentation for Cardiac MRI.A. Mukhopadhyay, I. Öksüz, M. Bevilacqua, R. Dharmakumar, and S. Tsaftaris. MICCAI (3), volume 9351 of Lecture Notes in Computer Science, page 12-20. Springer, (2015)Magnetic Resonance Fingerprinting Using Recurrent Neural Networks.I. Öksüz, G. Cruz, J. Clough, A. Bustin, N. Fuin, R. Botnar, C. Prieto, A. King, and J. Schnabel. ISBI, page 1537-1540. IEEE, (2019)Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology.J. Clough, I. Öksüz, N. Byrne, J. Schnabel, and A. King. IPMI, volume 11492 of Lecture Notes in Computer Science, page 16-28. Springer, (2019)Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.I. Öksüz, B. Ruijsink, E. Puyol-Antón, J. Clough, G. Cruz, A. Bustin, C. Prieto, R. Botnar, D. Rueckert, J. Schnabel and 1 other author(s). Medical Image Analysis, (2019)Mechanically Powered Motion Imaging Phantoms: Proof of Concept.A. Gomez, C. Schmitz, M. Henningsson, J. Housden, Y. Noh, V. Zimmer, J. Clough, I. Öksüz, N. Toussaint, A. King and 1 other author(s). CoRR, (2019)Data-Driven Feature Learning for Myocardial Segmentation of CP-BOLD MRI.A. Mukhopadhyay, I. Öksüz, M. Bevilacqua, R. Dharmakumar, and S. Tsaftaris. FIMH, volume 9126 of Lecture Notes in Computer Science, page 189-197. Springer, (2015)MRI-TRUS Image Synthesis with Application to Image-Guided Prostate Intervention.J. Onofrey, I. Öksüz, S. Sarkar, R. Venkataraman, L. Staib, and X. Papademetris. SASHIMI@MICCAI, volume 9968 of Lecture Notes in Computer Science, page 157-166. (2016)Unsupervised Myocardial Segmentation for Cardiac BOLD.I. Öksüz, A. Mukhopadhyay, R. Dharmakumar, and S. Tsaftaris. IEEE Trans. Med. Imaging, 36 (11): 2228-2238 (2017)Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge.A. Suinesiaputra, P. Ablin, X. Albà, M. Alessandrini, J. Allen, W. Bai, S. Çimen, P. Claes, B. Cowan, J. D'hooge and 26 other author(s). IEEE J. Biomedical and Health Informatics, 22 (2): 503-515 (2018)High-quality segmentation of low quality cardiac MR images using k-space artefact correction.I. Öksüz, J. Clough, W. Bai, B. Ruijsink, E. Puyol-Antón, G. Cruz, C. Prieto, A. King, and J. Schnabel. MIDL, volume 102 of Proceedings of Machine Learning Research, page 380-389. PMLR, (2019)

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Disambiguation of "Öksüz, Ilkay"

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Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge.

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Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge.