4 papers
SUGFW+: An Uncertainty-guided Feature Weighting Framework for Cold Start Active Adaptation of SAM in Medical Image Segmentation
Xiaochuan Ma, Ning Zhu, Jia Fu +5
Cold Start Active Learning (CSAL) is important in improving the performance of a medical image segmentation model with low annotation budget by querying a small subset for annotati…
One Knob to Rule Them All: A Unified Optimal Transport View of Cold-Start Active Learning
Ning Zhu, Xiaochuan Ma, Juntao Xu +4
Cold-Start Active Learning (CSAL) aims to select a valuable subset from an unlabeled pool without any prior knowledge or human assistance. Existing methods take diverse routes base…
MedCAL-Bench: A Comprehensive Benchmark on Cold-Start Active Learning with Foundation Models for Medical Image Analysis
Ning Zhu, Xiaochuan Ma, Shaoting Zhang +1
Cold-Start Active Learning (CSAL) aims to select informative samples for annotation without prior knowledge, which is important for improving annotation efficiency and model perfor…
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…