ACROBAT - a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology

The ACROBAT data set consists of 4,212 whole slide images (WSIs) from 1,153 female primary breast cancer patients. The WSIs in the data set are available at 10X magnification and show tissue sections from breast cancer resection specimens stained with hematoxylin and eosin (H&E) or immunohistochemistry (IHC). For each patient, one WSI of H&E stained tissue and at least one one, and up to four, WSIs of corresponding tissue stained with the routine diagnostic stains ER, PGR, HER2 and KI67 are available. The data set was acquired as part of the CHIME study (chimestudy.se) and its primary purpose was to facilitate the ACROBAT WSI registration challenge (acrobat.grand-challenge.org). The histopathology slides originate from routine diagnostic pathology workflows and were digitised for research purposes at Karolinska Institutet (Stockholm, Sweden). The image acquisition process resembles the routine digital pathology image digitisation workflow, using three different Hamamatsu WSI scanners, specifically one NanoZoomer S360 and two NanoZoomer XR. The WSIs in this data set are accompanied by a data table with one row for each WSI, specifying an anonymised patient ID, the stain or IHC antibody type of each WSI, as well as the magnification and microns per pixel at each available resolution level. Automated registration algorithm performance evaluation is possible through the ACROBAT challenge website based on over 37,000 landmark pair annotations from 13 annotators. While the primary purpose of this data set was the development and evaluation of WSI registration methods, this data set has the potential to facilitate further research in the context of computational pathology, for example in the areas of stain-guided learning, virtual staining, unsupervised learning and stain-independent models.

The data set consists of three subsets, the training, validation and test set, based on the ACROBAT WSI registration challenge. There are 750 cases in the training set, for each of which one H&E WSI and one to four IHC WSIs are available, with 3406 WSIs in total. The validation set consists of 100 cases with 200 WSIs in total and the test set of 303 cases with 606 WSIs in total. Both for the validation and test set, one H&E WSI as well as one randomly selected IHC WSI is available.

WSIs were anonymised by deleting the associated macro images, by generating filenames with random case IDs and by overwriting meta data fields with potentially personal information. Hamamatsu NDPI files were then converted using libvips (libvips.org/). WSIs are available as generic tiled TIFF WSIs (openslide.org/formats/generic-tiff/) at 10X magnification and lower image levels.

The data set is available for download in seven separate ZIP archives, five for the training data (train_part1.zip (71.47 GB), train_part2.zip (70.59 GB), train_part3.zip (75.91 GB), train_part4.zip (71.63 GB) and train_part5.zip (69.09 GB)), one for the validation data (valid.zip 21.79 GB) and one for the test data (test.zip 68.11 GB).

File listings and checksums in SHA1 format are available for checking archive/data integrity when downloading.

While it would be helpful to notify SND of any publications using this data set by sending an email to [e-mail], please note that this is not required to use the data.

ACROBAT数据集包含4212张全视野数字切片（Whole Slide Image，WSI），取材自1153名女性原发性乳腺癌患者。本数据集内的WSI均为10倍放大倍率，展示的组织切片来自乳腺癌切除标本，经苏木精-伊红（hematoxylin and eosin，H&E）染色或免疫组织化学（immunohistochemistry，IHC）处理。每位患者对应1张H&E染色组织的WSI，以及至少1张、最多4张对应组织的WSI，这些WSI采用临床常规诊断染色标志物ER、PGR、HER2及KI67进行染色。

本数据集采集自CHIME研究（chimestudy.se），其核心初衷是支持ACROBAT WSI配准挑战赛（acrobat.grand-challenge.org）的开展。这些病理组织切片均来源于临床常规诊断病理流程，由瑞典斯德哥尔摩卡罗林斯卡学院为研究目的完成数字化扫描。图像采集流程贴合临床常规数字化病理图像扫描流程，使用了三台不同型号的滨松（Hamamatsu）WSI扫描仪，具体为1台NanoZoomer S360与2台NanoZoomer XR。

本数据集配套包含一张数据表格，每行对应一张WSI，标注了匿名化患者ID、每张WSI的染色类型或IHC抗体种类，以及各分辨率层级下的放大倍率与每像素微米数。依托13名标注人员标注的超37000组地标对标注信息，可通过ACROBAT挑战赛官网完成自动化配准算法的性能评估。尽管本数据集的核心用途是开发与评估WSI配准方法，但它也有望推动计算病理学领域的更多研究，例如染色引导学习、虚拟染色、无监督学习以及不依赖染色的模型等方向。

本数据集基于ACROBAT WSI配准挑战赛划分为三个子集：训练集、验证集与测试集。训练集包含750个病例，每个病例对应1张H&E染色WSI与1至4张IHC染色WSI，总计3406张WSI。验证集包含100个病例，总计200张WSI；测试集包含303个病例，总计606张WSI。验证集与测试集的每个病例均提供1张H&E染色WSI与1张随机选取的IHC染色WSI。

WSI的匿名化处理方式包括：删除配套的宏观图像、使用随机病例ID生成文件名，以及覆盖包含潜在个人信息的元数据字段。随后使用libvips库（libvips.org/）将滨松NDPI格式文件转换为通用格式。本数据集的WSI以通用分块TIFF格式（openslide.org/formats/generic-tiff/）提供，包含10倍放大倍率及更低分辨率层级的图像。

本数据集以7个独立ZIP压缩包提供下载：5个训练数据压缩包（train_part1.zip，71.47 GB；train_part2.zip，70.59 GB；train_part3.zip，75.91 GB；train_part4.zip，71.63 GB；train_part5.zip，69.09 GB）、1个验证数据压缩包（valid.zip，21.79 GB）与1个测试数据压缩包（test.zip，68.11 GB）。下载时可通过提供的文件列表与SHA1格式校验和验证压缩包及数据的完整性。

若您使用本数据集发表研究成果，可通过发送邮件至[e-mail]告知SND，但此操作并非使用本数据集的强制要求。

搜集汇总

背景与挑战

背景概述

ACROBAT是一个用于计算病理学的多染色乳腺癌组织学全切片图像数据集，包含来自1,153名患者的4,212张图像，涵盖H&E和免疫组化染色。该数据集主要用于全切片图像配准挑战，支持染色引导学习、虚拟染色等研究，并已按训练、验证和测试集划分，总大小约448.6 GiB。