2 papers
cs.CV2025
Class Incremental Medical Image Segmentation via Prototype-Guided Calibration and Dual-Aligned Distillation
Shengqian Zhu, Chengrong Yu, Qiang Wang +6
Class incremental medical image segmentation (CIMIS) aims to preserve knowledge of previously learned classes while learning new ones without relying on old-class labels. However,…
cs.CV2025
Exploiting Unlabeled Structures through Task Consistency Training for Versatile Medical Image Segmentation
Shengqian Zhu, Jiafei Wu, Xiaogang Xu +5
Versatile medical image segmentation (VMIS) targets the segmentation of multiple classes, while obtaining full annotations for all classes is often impractical due to the time and…