27 citations · 32 across the 5 of their papers we have counts for
5 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…
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…
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…
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.…