27 citations · 42 across the 13 of their papers we have counts for
9 papers · 1 filter
Towards Computation- and Communication-efficient Computational Pathology
Chu Han, Bingchao Zhao, Jiatai Lin +9
Despite the impressive performance across a wide range of applications, current computational pathology models face significant diagnostic efficiency challenges due to their relian…
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…
HoVer-Trans: Anatomy-aware HoVer-Transformer for ROI-free Breast Cancer Diagnosis in Ultrasound Images
Yuhao Mo, Chu Han, Yu Liu +14
Ultrasonography is an important routine examination for breast cancer diagnosis, due to its non-invasive, radiation-free and low-cost properties. However, the diagnostic accuracy o…
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…
A Standardized Pipeline for Colon Nuclei Identification and Counting Challenge
Jijun Cheng, Xipeng Pan, Feihu Hou +5
Nuclear segmentation and classification is an essential step for computational pathology. TIA lab from Warwick University organized a nuclear segmentation and classification challe…
RestainNet: a self-supervised digital re-stainer for stain normalization
Bingchao Zhao, Jiatai Lin, Changhong Liang +8
Color inconsistency is an inevitable challenge in computational pathology, which generally happens because of stain intensity variations or sections scanned by different scanners.…
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…
Rethinking Annotation Granularity for Overcoming Shortcuts in Deep Learning-based Radiograph Diagnosis: A Multicenter Study
Luyang Luo, Hao Chen, Yongjie Xiao +10
Two DL models were developed using radiograph-level annotations (yes or no disease) and fine-grained lesion-level annotations (lesion bounding boxes), respectively named CheXNet an…