4 papers
EndoCIL: A Class-Incremental Learning Framework for Endoscopic Image Classification
Bingrong Liu, Jun Shi, Yushan Zheng
Class-incremental learning (CIL) for endoscopic image analysis is crucial for real-world clinical applications, where diagnostic models should continuously adapt to evolving clinic…
Promptable Representation Distribution Learning and Data Augmentation for Gigapixel Histopathology WSI Analysis
Kunming Tang, Zhiguo Jiang, Jun Shi +3
Gigapixel image analysis, particularly for whole slide images (WSIs), often relies on multiple instance learning (MIL). Under the paradigm of MIL, patch image representations are e…
Pan-cancer Histopathology WSI Pre-training with Position-aware Masked Autoencoder
Kun Wu, Zhiguo Jiang, Kunming Tang +5
Large-scale pre-training models have promoted the development of histopathology image analysis. However, existing self-supervised methods for histopathology images primarily focus…
Slide-based Graph Collaborative Training for Histopathology Whole Slide Image Analysis
Jun Shi, Tong Shu, Zhiguo Jiang +3
The development of computational pathology lies in the consensus that pathological characteristics of tumors are significant guidance for cancer diagnostics. Most existing research…