MItosis DOmain Generalization Challenge 2022 (MICCAI MIDOG 2022), Training data set (PNG version)

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).

本数据集为与2022年国际医学图像计算和计算机辅助干预会议（MICCAI 2022）联合举办的有丝分裂域泛化（MItosis DOmain Generalization, MIDOG）挑战赛2022届的训练数据集。结构化挑战赛说明可参见DOI：10.5281/zenodo.6362337。

本训练集共包含405例肿瘤病例，涵盖6种肿瘤类型：
- 犬肺癌（44例，采用3DHistech Pannoramic Scan II扫描仪扫描）
- 人类乳腺癌（150例，使用三台扫描仪完成扫描，为MIDOG2021数据集的组成部分）
- 犬淋巴瘤（55例，采用3DHistech Pannoramic Scan II扫描仪扫描）
- 人类神经内分泌肿瘤（55例，使用Hamamatsu NanoZoomer XR扫描仪扫描）
- 犬皮肤肥大细胞瘤（50例，采用Aperio ScanScope CS2扫描仪扫描）
- 人类黑色素瘤（51例，使用Hamamatsu NanoZoomer XR扫描仪扫描，不提供标注）

根据埃尔斯顿与埃利斯（Elston and Ellis）分级方案，经过专业训练的病理学家从每一张全切片图像（Whole Slide Image, WSI）中选取了面积为2mm²的区域，该区域大致对应10个高倍视野。鉴于Zenodo平台对数据集大小的限制，我们将该区域裁剪为PNG格式文件并纳入本数据集。每个文件均标注了原始扫描图像的分辨率（单位：每英寸点数，DPI）。

本训练集共包含9501个有丝分裂象（mitotic figures, MF）与11051个困难样本（非有丝分裂象）。所有标注均采用MS COCO JSON格式以及SQLite数据库（SlideRunner格式）进行提供。