12 citations · 16 across the 3 of their papers we have counts for
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cs.CV2023★ 3 cited
Self-training with dual uncertainty for semi-supervised medical image segmentation
Zhanhong Qiu, Haitao Gan, Ming Shi +2
In the field of semi-supervised medical image segmentation, the shortage of labeled data is the fundamental problem. How to effectively learn image features from unlabeled images t…
cs.CV2022★ 1 cited
Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images
Min Shi, Anagha Lokhande, Mojtaba S. Fazli +10
Ophthalmic images and derivatives such as the retinal nerve fiber layer (RNFL) thickness map are crucial for detecting and monitoring ophthalmic diseases (e.g., glaucoma). For comp…