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Shengcong Chen
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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
17412018
Dual-force convolutional neural networks for accurate brain tumor segmentation
S Chen, C Ding, M Liu
Pattern Recognition 88, 90-100, 2019
1812019
Learning contextual and attentive information for brain tumor segmentation
C Zhou, S Chen, C Ding, D Tao
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019
1352019
Boundary-assisted region proposal networks for nucleus segmentation
S Chen, C Ding, D Tao
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
332020
CPP-net: Context-aware polygon proposal network for nucleus segmentation
S Chen, C Ding, M Liu, J Cheng, D Tao
IEEE Transactions on Image Processing 32, 980-994, 2023
322023
Brain tumor segmentation with label distribution learning and multi-level feature representation
S Chen, C Ding, C Zhou
Proceedings of the International MICCAI BraTS Challenge, 2017
62017
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