Ankara university NuSeC and MiDeSeC datasets.zip

The NuSeC (Nuclei Segmentation and Classification) and MiDeSeC (Mitosis Detection, Segmentation and Classification) datasets were created as part of the TÜBİTAK project 121E379, titled “Development of Deep Learning-Based Methodology for the Detection of Breast Cancer in Histopathology Images.” They are designed to support research in digital pathology by enabling the development and evaluation of deep learning models for breast cancer diagnosis.Purpose: To provide annotated data for training/testing AI models in nuclei segmentation, classification, and mitosis detection.To assist in the automated grading of breast cancer from histopathology images.To reduce the workload and increase the accuracy of pathologists’ assessments.If you use these datasets in your work, please cite the following studies:NuSeC: A Dataset for Nuclei Segmentation in Breast Cancer Histopathology ImagesMiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images"Deep Learning Methodologies for Nuclei Segmentation and Mitosis Detection in Histopathological Images Analysis."