7 papers
Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey
Guohui Cai, Ying Cai, Zeyu Zhang +5
Lung cancer remains one of the leading causes of morbidity and mortality worldwide, making early diagnosis critical for improving therapeutic outcomes and patient prognosis. Comput…
SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation
Hongjie Zhu, Xiwei Liu, Rundong Xue +5
In the era of information explosion, efficiently leveraging large-scale unlabeled data while minimizing the reliance on high-quality pixel-level annotations remains a critical chal…
Dynamic Domain Adaptation-Driven Physics-Informed Graph Representation Learning for AC-OPF
Hongjie Zhu, Zezheng Zhang, Zeyu Zhang +6
Alternating Current Optimal Power Flow (AC-OPF) aims to optimize generator power outputs by utilizing the non-linear relationships between voltage magnitudes and phase angles in a…
DOEI: Dual Optimization of Embedding Information for Attention-Enhanced Class Activation Maps
Hongjie Zhu, Zeyu Zhang, Guansong Pang +6
Weakly supervised semantic segmentation (WSSS) typically utilizes limited semantic annotations to obtain initial Class Activation Maps (CAMs). However, due to the inadequate coupli…
MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule
Guohui Cai, Ruicheng Zhang, Hongyang He +8
Pulmonary nodules are critical indicators for the early diagnosis of lung cancer, making their detection essential for timely treatment. However, traditional CT imaging methods suf…
SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies
Shengbo Tan, Rundong Xue, Shipeng Luo +7
Hepatic vessels in computed tomography scans often suffer from image fragmentation and noise interference, making it difficult to maintain vessel integrity and posing significant c…