Navigating challenges in mitosis detection: A Difficulty-Aware Learning Paradigm
Authors:
- Kang YuKYKang Yu
- Bingbing LiBLBingbing Li
- Xipeng PanXPXipeng Pan
- Rushi LanRLRushi Lan
- Huadeng WangHWHuadeng Wang
- Junlin GuanJGJunlin Guan
- 13 October 2025
- journal article
- Published by Elsevier in Biomedical Signal Processing and Control
- Vol. 113
Abstract
No abstract availableFunding Information
- Science and Technology Major Project of Guangxi (GuikeAA24263013)
- Science and Technology Major Project of Guangxi (GuikeAA24263033)
- Science and Technology Major Project of Guangxi (GuikeAA23073007)
- Natural Science Foundation of Guangxi Province (2024GXNSFFA010014)
- Natural Science Foundation of Guangxi Province (2024GXNSFAA010342)
- National Natural Science Foundation of China (62362014)
- Natural Science Foundation of Guangxi Zhuang Autonomous Region
This publication has 26 references indexed in Scilit:
- Weakly supervised histopathology tissue semantic segmentation with multi-scale voting and online noise suppressionEngineering Applications of Artificial Intelligence, 2025
- Rethinking mitosis detection: Towards diverse data and feature representation for better domain generalizationArtificial Intelligence in Medicine, 2025
- Segmentation of coronary arteries from X-ray angiographic images using density based spatial clustering of applications with noise (DBSCAN)Biomedical Signal Processing and Control, 2024
- Uninformed Teacher-Student for hard-samples distillation in weakly supervised mitosis localizationComputerized Medical Imaging and Graphics, 2024
- A novel dataset and a two-stage mitosis nuclei detection method based on hybrid anchor branchBiomedical Signal Processing and Control, 2023
- Novel architecture with selected feature vector for effective classification of mitotic and non-mitotic cells in breast cancer histology imagesBiomedical Signal Processing and Control, 2022
- A deep learning approach for mitosis detection: Application in tumor proliferation prediction from whole slide imagesArtificial Intelligence in Medicine, 2021
- MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology imagesMedical & Biological Engineering & Computing, 2020
- Weakly supervised mitosis detection in breast histopathology images using concentric lossMedical Image Analysis, 2019
- DeepMitosis: Mitosis detection via deep detection, verification and segmentation networksMedical Image Analysis, 2018