LungHist700: A Dataset of Histological Images for Deep Learning in Pulmonary Pathology

We present a comprehensive dataset of 691 histopathological images of the lungs, encompassing three categories: adenocarcinomas, squamous cell carcinomas, and normal lung tissues from 45 patients. These images are of high resolution (1200x1600 pixels) and are subdivided into three levels of differentiation for both pathological sets: well differentiated, moderately differentiated, and poorly differentiated. This provides a total of seven classes for classification purposes. A significant portion of the images are at 20x magnification, while others are at 40x magnification, reflecting the diversity of histopathological samples encountered in real clinical practice.本研究构建了一套包含691张肺部组织病理学图像的综合性数据集，样本取自45名患者，涵盖三大类组织：肺腺癌（adenocarcinomas）、肺鳞状细胞癌（squamous cell carcinomas）以及正常肺组织。该数据集图像分辨率均为1200×1600像素，且针对两类病理组织样本（腺癌与鳞状细胞癌）分别按照细胞分化程度细分为三级：高分化（well differentiated）、中分化（moderately differentiated）与低分化（poorly differentiated）。据此，本数据集共计7个分类类别。其中大部分图像的拍摄放大倍数为20倍，剩余部分为40倍，能够真实反映临床实际工作中常见的组织病理学样本多样性。