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Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.

X. Zhuang, J. Xu, X. Luo, C. Chen, C. Ouyang, D. Rueckert, V. Campello, K. Lekadir, S. Vesal, N. Ravikumar, Y. Liu, G. Luo, J. Chen, H. Li, B. Ly, M. Sermesant, H. Roth, W. Zhu, J. Wang, X. Ding, X. Wang, S. Yang, and L. Li. Medical Image Anal., (2022)

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Hosen Sulaiman

Vesal Khorsand

Marjo Vesalainen

Jenny Sulaiman

Sulaiman Alateyah

Other publications of authors with the same name

Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimization for Multi-Modal Cardiac Image Segmentation.S. Vesal, M. Gu, R. Kosti, A. Maier, and N. Ravikumar. IEEE Trans. Medical Imaging, 40 (7): 1838-1851 (2021)Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.A. Hering, L. Hansen, T. Mok, A. Chung, H. Siebert, S. Häger, A. Lange, S. Kuckertz, S. Heldmann, W. Shao and 37 other author(s). CoRR, (2021)Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge.X. Zhuang, J. Xu, X. Luo, C. Chen, C. Ouyang, D. Rueckert, V. Campello, K. Lekadir, S. Vesal, N. Ravikumar and 13 other author(s). CoRR, (2020)Unsupervised Domain Adaptation Using Soft-Labeled Contrastive Learning with Reversed Monte Carlo Method for Cardiac Image Segmentation.M. Gu, M. Thies, S. Mei, F. Wagner, M. Fan, Y. Sun, Z. Pan, S. Vesal, R. Kosti, D. Possart and 2 other author(s). MICCAI (9), volume 15009 of Lecture Notes in Computer Science, page 681-691. Springer, (2024)Mammographic breast density classification using a deep neural network: assessment on the basis of inter-observer variability.N. Kaiser, A. Fieselmann, S. Vesal, N. Ravikumar, L. Ritschl, S. Kappler, and A. Maier. Image Perception, Observer Performance, and Technology Assessment, volume 10952 of SPIE Proceedings, page 109520O. SPIE, (2019)Deep Learning-based Denoising of Mammographic Images using Physics-driven Data Augmentation.D. Eckert, S. Vesal, L. Ritschl, S. Kappler, and A. Maier. CoRR, (2019)Classification of Breast Cancer Histology Images Using Transfer Learning.S. Vesal, N. Ravikumar, A. Davari, S. Ellmann, and A. Maier. ICIAR, volume 10882 of Lecture Notes in Computer Science, page 812-819. Springer, (2018)Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.X. Zhuang, J. Xu, X. Luo, C. Chen, C. Ouyang, D. Rueckert, V. Campello, K. Lekadir, S. Vesal, N. Ravikumar and 13 other author(s). Medical Image Anal., (2022)A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT.S. Vesal, N. Ravikumar, and A. Maier. SegTHOR@ISBI, volume 2349 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)The Learn2Reg 2021 MICCAI Grand Challenge (PIMed Team).W. Shao, S. Vesal, D. Lim, C. Li, N. Golestani, A. Alsinan, R. Fan, G. Sonn, and M. Rusu. MIDOG/MOOD/Learn2Reg@MICCAI, volume 13166 of Lecture Notes in Computer Science, page 168-173. Springer, (2021)

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Disambiguation of "Vesal, Sulaiman"

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Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.

Please choose a person to relate this publication to

Hosen Sulaiman

Vesal Khorsand

Marjo Vesalainen

Jenny Sulaiman

Sulaiman Alateyah

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Vesal, Sulaiman"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.

Please choose a person to relate this publication to

Hosen Sulaiman

Vesal Khorsand

Marjo Vesalainen

Jenny Sulaiman

Sulaiman Alateyah

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
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Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.