6 citations · 8 across the 4 of their papers we have counts for
5 papers
Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks
Junlin Hou, Sicen Liu, Yequan Bie +4
The increasing demand for transparent and reliable models, particularly in high-stakes decision-making areas such as medical image analysis, has led to the emergence of eXplainable…
SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition
Shu Yang, Zhiyuan Cai, Luyang Luo +3
Capitalizing on image-level pre-trained models for various downstream tasks has recently emerged with promising performance. However, the paradigm of "image pre-training followed b…
Surgformer: Surgical Transformer with Hierarchical Temporal Attention for Surgical Phase Recognition
Shu Yang, Luyang Luo, Qiong Wang +1
Existing state-of-the-art methods for surgical phase recognition either rely on the extraction of spatial-temporal features at a short-range temporal resolution or adopt the sequen…
A Large Model for Non-invasive and Personalized Management of Breast Cancer from Multiparametric MRI
Luyang Luo, Mingxiang Wu, Mei Li +8
Breast Magnetic Resonance Imaging (MRI) demonstrates the highest sensitivity for breast cancer detection among imaging modalities and is standard practice for high-risk women. Inte…
Enable the Right to be Forgotten with Federated Client Unlearning in Medical Imaging
Zhipeng Deng, Luyang Luo, Hao Chen
The right to be forgotten, as stated in most data regulations, poses an underexplored challenge in federated learning (FL), leading to the development of federated unlearning (FU).…