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The MIDOG++ dataset represents an extension of the data set used in the MIDOG 2021 and 2022 challenges. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The human and canine samples were processed and stained at different human and veterinary pathology laboratories with standard H&E dye and digitized with different digital whole slide image scanners. We provide labels for 11,937 mitotic figures that have been differentiated against 14,351 imposter cells in a blinded consensus by two pathologists and a final decision by a third pathologist for disagreed labels.

MIDOG++数据集是MIDOG 2021与2022挑战赛所用数据集的扩展版本。我们提供了来自7种形态学特征各异的肿瘤类型的503份组织学标本的感兴趣区域（Region of Interest, ROI）图像，涵盖乳腺癌、肺癌、淋巴肉瘤、神经内分泌肿瘤、皮肤肥大细胞瘤、皮肤黑色素瘤以及（皮下）软组织肉瘤。所有人类与犬类标本均在多家人类病理学及兽医学病理学实验室中，采用标准苏木精-伊红（Hematoxylin-Eosin, H&E）染色剂完成染色与前处理，并通过多款数字化全玻片扫描设备完成数字化扫描。本数据集包含11937个有丝分裂象（mitotic figures）的标注标签，上述标签由两名病理学家以盲法共识的方式，与14351个伪有丝分裂细胞进行区分；对于标注存在分歧的样本，则由第三名病理学家作出最终判定。