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Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation.

K. Kamnitsas, C. Ledig, V. Newcombe, J. Simpson, A. Kane, D. Menon, D. Rueckert, and B. Glocker. CoRR, (2016)

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Katja Ledig

Astrid Lediger

Rudolf Ledig

Roland Ledig

Elfriede Ledig

Other publications of authors with the same name

A Semi-supervised Large Margin Algorithm for White Matter Hyperintensity Segmentation.C. Qin, R. Moreno, C. Bowles, C. Ledig, P. Scheltens, F. Barkhof, H. Rhodius-Meester, B. Tijms, A. Lemstra, W. van der Flier and 2 other author(s). MLMI@MICCAI, volume 10019 of Lecture Notes in Computer Science, page 104-112. (2016)Multi-atlas segmentation with augmented features for cardiac MR images.W. Bai, W. Shi, C. Ledig, and D. Rueckert. Medical Image Anal., 19 (1): 98-109 (2015)Generative Image Translation for Data Augmentation of Bone Lesion Pathology.A. Gupta, S. Venkatesh, S. Chopra, and C. Ledig. MIDL, volume 102 of Proceedings of Machine Learning Research, page 225-235. PMLR, (2019)Robust multi-structure segmentation of magnetic resonance brain images.C. Ledig. Imperial College London, UK, (2015)British Library, EThOS.Contusion segmentation from subjects with Traumatic Brain Injury: A random forest framework.A. Rao, C. Ledig, V. Newcombe, D. Menon, and D. Rueckert. ISBI, page 333-336. IEEE, (2014)Unsupervised domain adaptation in brain lesion segmentation with adversarial networks.K. Kamnitsas, C. Baumgartner, C. Ledig, V. Newcombe, J. Simpson, A. Kane, D. Menon, A. Nori, A. Criminisi, D. Rueckert and 1 other author(s). CoRR, (2016)Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models.C. Biffi, J. Cerrolaza, G. Tarroni, W. Bai, A. de Marvao, O. Oktay, C. Ledig, L. Folgoc, K. Kamnitsas, G. Doumou and 5 other author(s). IEEE Trans. Medical Imaging, 39 (6): 2088-2099 (2020)Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation.K. Kamnitsas, C. Ledig, V. Newcombe, J. Simpson, A. Kane, D. Menon, D. Rueckert, and B. Glocker. Medical Image Anal., (2017)Automatic quantification of normal cortical folding patterns from fetal brain MRI.R. Wright, V. Kyriakopoulou, C. Ledig, M. Rutherford, J. Hajnal, D. Rueckert, and P. Aljabar. NeuroImage, (2014)Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks.K. Kamnitsas, C. Baumgartner, C. Ledig, V. Newcombe, J. Simpson, A. Kane, D. Menon, A. Nori, A. Criminisi, D. Rueckert and 1 other author(s). IPMI, volume 10265 of Lecture Notes in Computer Science, page 597-609. Springer, (2017)

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Disambiguation of "Ledig, Christian"

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Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation.

Please choose a person to relate this publication to

Katja Ledig

Astrid Lediger

Rudolf Ledig

Roland Ledig

Elfriede Ledig

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Ledig, Christian"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation.

Please choose a person to relate this publication to

Katja Ledig

Astrid Lediger

Rudolf Ledig

Roland Ledig

Elfriede Ledig

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
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APA
Chicago
DIN 1505
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MSOffice XML

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation.