15 citations · 38 across the 11 of their papers we have counts for
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cs.CV2021
Source-free unsupervised domain adaptation for cross-modality abdominal multi-organ segmentation
Jin Hong, Yu-Dong Zhang, Weitian Chen
Domain adaptation is crucial for transferring the knowledge from the source labeled CT dataset to the target unlabeled MR dataset in abdominal multi-organ segmentation. Meanwhile,…
eess.IV2021
Multipath CNN with alpha matte inference for knee tissue segmentation from MRI
Sheheryar Khan, Basim Azam, Yongcheng Yao +1
Precise segmentation of knee tissues from magnetic resonance imaging (MRI) is critical in quantitative imaging and diagnosis. Convolutional neural networks (CNNs), which are state…
cs.CV2021
Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learning
Jin Hong, Simon Chun-Ho Yu, Weitian Chen
Liver segmentation on images acquired using computed tomography (CT) and magnetic resonance imaging (MRI) plays an important role in clinical management of liver diseases. Compared…