4 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
MG-3D: Multi-Grained Knowledge-Enhanced 3D Medical Vision-Language Pre-training
Xuefeng Ni, Linshan Wu, Jiaxin Zhuang +6
3D medical image analysis is pivotal in numerous clinical applications. However, the scarcity of labeled data and limited generalization capabilities hinder the advancement of AI-e…
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…
MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysis
Jiaxin Zhuang, Linshan Wu, Qiong Wang +4
The Vision Transformer (ViT) has demonstrated remarkable performance in Self-Supervised Learning (SSL) for 3D medical image analysis. Masked AutoEncoder (MAE) for feature pre-train…
GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
Sunan He, Yuxiang Nie, Hongmei Wang +21
Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of m…