8 papers
CoBa: Cost-Effective Test-Time Scaling via Compute-Balanced Routing
Yan Zhou, Yue Ouyang, Kaiyang Zheng +1
Test-time scaling is often implemented by spending more compute along one axis: sampling more solutions, extending a chain of thought, or applying a stronger evaluator. Under a fix…
MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
Cenwei Zhang, Suncheng Xiang, Lei You
Medical segmentation foundation models such as SAM and MedSAM provide strong prompt-driven segmentation, but their image encoders are still too large for many clinical settings. Co…
BMDS-Net:Deployment-aware multi-modal brain tumor segmentation with adaptive fusion,decoder regularization,and Bayesian calibration
Yan Zhou, Zhen Huang, Yingqiu Li +3
Multi-modal MRI enables detailed brain tumor sub-region segmentation, but clinical deployment remains affected by missing sequences,boundary errors, and overconfident predictions.…
GPF-Net: Gated Progressive Fusion Learning for Polyp Re-Identification
Suncheng Xiang, Xiaoyang Wang, Junjie Jiang +2
Colonoscopic Polyp Re-Identification aims to match the same polyp from a large gallery with images from different views taken using different cameras, which plays an important role…
MicroAUNet: Boundary-Enhanced Multi-scale Fusion with Knowledge Distillation for Colonoscopy Polyp Image Segmentation
Ziyi Wang, Yuanmei Zhang, Dorna Esrafilzadeh +5
Early and accurate segmentation of colorectal polyps is critical for reducing colorectal cancer mortality, which has been extensively explored by academia and industry. However, cu…
BALR-SAM: Boundary-Aware Low-Rank Adaptation of SAM for Resource-Efficient Medical Image Segmentation
Zelin Liu, Sicheng Dong, Bocheng Li +4
Vision foundation models like the Segment Anything Model (SAM), pretrained on large-scale natural image datasets, often struggle in medical image segmentation due to a lack of doma…