27 citations · 32 across the 7 of their papers we have counts for
7 papers
BroadCAM: Outcome-agnostic Class Activation Mapping for Small-scale Weakly Supervised Applications
Jiatai Lin, Guoqiang Han, Xuemiao Xu +5
Class activation mapping~(CAM), a visualization technique for interpreting deep learning models, is now commonly used for weakly supervised semantic segmentation~(WSSS) and object…
Rethinking Mitosis Detection: Towards Diverse Data and Feature Representation
Hao Wang, Jiatai Lin, Danyi Li +11
Mitosis detection is one of the fundamental tasks in computational pathology, which is extremely challenging due to the heterogeneity of mitotic cell. Most of the current studies s…
FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification
Tianpeng Deng, Yanqi Huang, Guoqiang Han +7
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning-based models have achieved superior performance but centralized training wit…
CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation
Jianwei Lin, Jiatai Lin, Cheng Lu +12
Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain tumor diagnosis, cancer management and research purposes. With the great success of the ten-ye…
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma
Chu Han, Xipeng Pan, Lixu Yan +40
Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma (LUAD) is the most common subtype. Exploiting the potential value of the histopathology images can pr…
PDBL: Improving Histopathological Tissue Classification with Plug-and-Play Pyramidal Deep-Broad Learning
Jiatai Lin, Guoqiang Han, Xipeng Pan +11
Histopathological tissue classification is a fundamental task in pathomics cancer research. Precisely differentiating different tissue types is a benefit for the downstream researc…
Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification Labels
Chu Han, Jiatai Lin, Jinhai Mai +15
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance with dense pixel-level annotati…