27 citations · 35 across the 7 of their papers we have counts for
4 papers · 1 filter
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…