27 citations · 45 across the 9 of their papers we have counts for
9 papers
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…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
A novel dataset and a two-stage mitosis nuclei detection method based on hybrid anchor branch
Huadeng Wang, Hao Xu, Bingbing Li +4
Mitosis detection is one of the challenging problems in computational pathology, and mitotic count is an important index of cancer grading for pathologists. However, current counts…
A Novel Dataset and a Deep Learning Method for Mitosis Nuclei Segmentation and Classification
Huadeng Wang, Zhipeng Liu, Rushi Lan +4
Mitosis nuclei count is one of the important indicators for the pathological diagnosis of breast cancer. The manual annotation needs experienced pathologists, which is very time-co…
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.…