24 citations · 46 across the 16 of their papers we have counts for
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cs.CV2025
MetaSSL: A General Heterogeneous Loss for Semi-Supervised Medical Image Segmentation
Weiren Zhao, Lanfeng Zhong, Xin Liao +4
Semi-Supervised Learning (SSL) is important for reducing the annotation cost for medical image segmentation models. State-of-the-art SSL methods such as Mean Teacher, FixMatch and…
cs.CV2025
Dynamic Gradient Sparsification Training for Few-Shot Fine-tuning of CT Lymph Node Segmentation Foundation Model
Zihao Luo, Zijun Gao, Wenjun Liao +3
Accurate lymph node (LN) segmentation is critical in radiotherapy treatment and prognosis analysis, but is limited by the need for large annotated datasets. While deep learning-bas…
cs.CV2025
CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation
Xiaochuan Ma, Jia Fu, Wenjun Liao +2
Brain tumor segmentation is important for diagnosis of the tumor, and current deep-learning methods rely on a large set of annotated images for training, with high annotation costs…