AIMC Topic: Mitosis
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Mitosis detection and classification for breast cancer diagnosis: What we know and what is next.
Computers in biology and medicine
Jun 1, 2025
Breast cancer is the second most deadly malignancy in women, behind lung cancer. Despite significant improvements in medical research, breast cancer is still accurately diagnosed with histological analysis. During this procedure, pathologists examine...
pcnaDeep: a fast and robust single-cell tracking method using deep-learning mediated cell cycle profiling.
Bioinformatics (Oxford, England)
Oct 14, 2022
SUMMARY: Computational methods that track single cells and quantify fluorescent biosensors in time-lapse microscopy images have revolutionized our approach in studying the molecular control of cellular decisions. One barrier that limits the adoption ...
Transfer learning based deep CNN for segmentation and detection of mitoses in breast cancer histopathological images.
Microscopy (Oxford, England)
Jun 1, 2019
Segmentation and detection of mitotic nuclei is a challenging task. To address this problem, a Transfer Learning based fast and accurate system is proposed. To give the classifier a balanced dataset, this work exploits the concept of Transfer Learnin...
Detection of mitotic nuclei in breast histopathology images using localized ACM and Random Kitchen Sink based classifier.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmen...
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