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This is the training dataset of the MItosis DOmain Generalization (MIDOG) challenge 2022, held in conjunction with MICCAI 2022. Please find the structured challenge description at 10.5281/zenodo.6362337. The training set consists of 405 tumor cases in total across six tumor types: Canine Lung Cancer (44 cases, scanned with 3DHistech Pannoramic Scan II) Human Breast Cancer (150 cases, scanned using three scanners, part of MIDOG2021 dataset) Canine Lymphoma (55 cases, scanned with 3DHistech Pannoramic Scan II) Human neuroendocrine tumor (55 cases, scanned with Hamamatsu NanoZoomer XR) Canine Cutaneous Mast Cell Tumor (50 cases, scanned with Aperio ScanScope CS2) Human melanoma (51 cases, scanned with Hamamatsu NanoZoomer XR) (no labels provided) From each WSI, a trained pathologist selected an area of 2mm² corresponding to approximately 10 high power fields, according to the grading scheme of Elston and Ellis. We cropped this area and provide it as PNG files in this data set due to restrictions in data set size on zenodo. Each file includes the resolution (in dots per inch, DPI) of the original scanned images. The training set contains 9501 mitotic figures (MF) and 11051 hard examples (non-mitotic figures). All annotations are provided in MS COCO JSON format and as SQLITE database (SlideRunner format).
mitotic figure, histopathology, domain generalization
mitotic figure, histopathology, domain generalization
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