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20212026
most citedWSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

27 citations · 40 across the 12 of their papers we have counts for

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9 papers · 1 filter

eess.IV2025

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…

eess.IV2023

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…

eess.IV2022★ 4 cited

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…

eess.IV2022★ 6 cited

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…

eess.IV2022★ 27 cited

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…

eess.IV2022★ 2 cited

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…

eess.IV2022

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.…

eess.IV2021

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…

eess.IV2021

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…