Jun Ma
Jun Ma
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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge
N Heller, F Isensee, KH Maier-Hein, X Hou, C Xie, F Li, Y Nan, G Mu, ...
Medical image analysis 67, 101821, 2021
Loss odyssey in medical image segmentation
J Ma, J Chen, M Ng, R Huang, Y Li, C Li, X Yang, AL Martel
Medical Image Analysis 71, 102035, 2021
Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation
J Ma, Y Wang, X An, C Ge, Z Yu, J Chen, Q Zhu, G Dong, J He, Z He, ...
Medical Physics, 2020
Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge
VM Campello, P Gkontra, C Izquierdo, C Martin-Isla, A Sojoudi, PM Full, ...
IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021
Abdomenct-1k: Is abdominal organ segmentation a solved problem?
J Ma, Y Zhang, S Gu, C Zhu, C Ge, Y Zhang, X An, C Wang, Q Wang, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 6695 …, 2021
Segment anything in medical images
J Ma, B Wang
arXiv preprint arXiv:2304.12306, 2023
Head and neck tumor segmentation in PET/CT: the HECKTOR challenge
V Oreiller, V Andrearczyk, M Jreige, S Boughdad, H Elhalawani, J Castelli, ...
Medical image analysis 77, 102336, 2022
Fast and low-GPU-memory abdomen CT organ segmentation: the flare challenge
J Ma, Y Zhang, S Gu, X An, Z Wang, C Ge, C Wang, F Zhang, Y Wang, ...
Medical Image Analysis 82, 102616, 2022
How distance transform maps boost segmentation CNNs: an empirical study
J Ma, Z Wei, Y Zhang, Y Wang, R Lv, C Zhu, C Gaoxiang, J Liu, C Peng, ...
Medical Imaging with Deep Learning, 479-492, 2020
Multi-site infant brain segmentation algorithms: the iSeg-2019 challenge
Y Sun, K Gao, Z Wu, G Li, X Zong, Z Lei, Y Wei, J Ma, X Yang, X Feng, ...
IEEE Transactions on Medical Imaging 40 (5), 1363-1376, 2021
Learning geodesic active contours for embedding object global information in segmentation CNNs
J Ma, J He, X Yang
IEEE Transactions on Medical Imaging 40 (1), 93-104, 2020
Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: the ADAM challenge
KM Timmins, IC van der Schaaf, E Bennink, YM Ruigrok, X An, ...
Neuroimage 238, 118216, 2021
Unleashing the strengths of unlabeled data in pan-cancer abdominal organ quantification: the flare22 challenge
J Ma, Y Zhang, S Gu, C Ge, S Ma, A Young, C Zhu, K Meng, X Yang, ...
arXiv preprint arXiv:2308.05862, 2023
Automated segmentation of normal and diseased coronary arteries–the asoca challenge
R Gharleghi, D Adikari, K Ellenberger, SY Ooi, C Ellis, CM Chen, R Gao, ...
Computerized Medical Imaging and Graphics 97, 102049, 2022
Cutting-edge 3D medical image segmentation methods in 2020: Are happy families all alike?
J Ma
arXiv preprint arXiv:2101.00232, 2021
Histogram matching augmentation for domain adaptation with application to multi-centre, multi-vendor and multi-disease cardiac image segmentation
J Ma
Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC …, 2021
Active contour regularized semi-supervised learning for COVID-19 CT infection segmentation with limited annotations
J Ma, Z Nie, C Wang, G Dong, Q Zhu, J He, L Gui, X Yang
Physics in Medicine & Biology 65 (22), 225034, 2020
Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge
A Lalande, Z Chen, T Pommier, T Decourselle, A Qayyum, M Salomon, ...
Medical Image Analysis 79, 102428, 2022
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