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Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach.

J. Duan, G. Bello, J. Schlemper, W. Bai, T. Dawes, C. Biffi, A. de Marvao, G. Doumou, D. O'Regan, and D. Rueckert. CoRR, (2018)

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Carlo Sibold University of Stuttgart

Carlo Cossu

Carlo Schmidt University of Stuttgart

Carlo Golini University of Stuttgart

Dr. -Ing. Carlo Sigolotto University of Stuttgart

Other publications of authors with the same name

Fetal Skull Reconstruction via Deep Convolutional Autoencoders.J. Cerrolaza, Y. Li, C. Biffi, A. Gómez, J. Matthew, M. Sinclair, C. Gupta, C. Knight, and D. Rueckert. EMBC, page 887-890. IEEE, (2018)Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling.C. Biffi, J. Cerrolaza, G. Tarroni, W. Bai, O. Oktay, L. Folgoc, K. Kamnitsas, A. de Marvao, G. Doumou, J. Duan and 4 other author(s). CoRR, (2019)Combining Deep Learning and Shape Priors for Bi-Ventricular Segmentation of Volumetric Cardiac Magnetic Resonance Images.J. Duan, J. Schlemper, W. Bai, T. Dawes, G. Bello, C. Biffi, G. Doumou, A. de Marvao, D. O'Regan, and D. Rueckert. ShapeMI@@MICCAI, volume 11167 of Lecture Notes in Computer Science, page 258-267. Springer, (2018)Three-dimensional cardiovascular imaging-genetics: a mass univariate framework.C. Biffi, A. de Marvao, M. Attard, T. Dawes, N. Whiffin, W. Bai, W. Shi, C. Francis, H. Meyer, R. Buchan and 3 other author(s). Bioinformatics, 34 (1): 97-103 (2018)Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation.C. Ouyang, K. Kamnitsas, C. Biffi, J. Duan, and D. Rueckert. CoRR, (2019)Generalising Deep Learning MRI Reconstruction across Different Domains.C. Ouyang, J. Schlemper, C. Biffi, G. Seegoolam, J. Caballero, A. Price, J. Hajnal, and D. Rueckert. CoRR, (2019)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, T. Dawes, C. Biffi, A. de Marvao, G. Doumou, D. O'Regan, and D. Rueckert. IEEE Trans. Med. Imaging, 38 (9): 2151-2164 (2019)Deep learning cardiac motion analysis for human survival prediction.G. Bello, T. Dawes, J. Duan, C. Biffi, A. de Marvao, L. Howard, J. Gibbs, M. Wilkins, S. Cook, D. Rueckert and 1 other author(s). CoRR, (2018)Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach.J. Duan, G. Bello, J. Schlemper, W. Bai, T. Dawes, C. Biffi, A. de Marvao, G. Doumou, D. O'Regan, and D. Rueckert. CoRR, (2018)3D Fetal Skull Reconstruction from 2DUS via Deep Conditional Generative Networks.J. Cerrolaza, Y. Li, C. Biffi, A. Gómez, M. Sinclair, J. Matthew, C. Knight, B. Kainz, and D. Rueckert. MICCAI (1), volume 11070 of Lecture Notes in Computer Science, page 383-391. Springer, (2018)

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Disambiguation of "Biffi, Carlo"

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Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach.

Please choose a person to relate this publication to

Carlo Sibold University of Stuttgart

Carlo Cossu

Carlo Schmidt University of Stuttgart

Carlo Golini University of Stuttgart

Dr. -Ing. Carlo Sigolotto University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Biffi, Carlo"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach.

Please choose a person to relate this publication to

Carlo Sibold University of Stuttgart

Carlo Cossu

Carlo Schmidt University of Stuttgart

Carlo Golini University of Stuttgart

Dr. -Ing. Carlo Sigolotto University of Stuttgart

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
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MSOffice XML

Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach.