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.

我们构建了一套包含691张肺部组织病理学（histopathological）图像的综合数据集，涵盖三类样本：取自45名患者的腺癌（adenocarcinomas）、鳞状细胞癌（squamous cell carcinomas）以及正常肺组织。所有图像均为1200×1600像素的高分辨率图像，且针对腺癌与鳞状细胞癌两类病理样本，分别划分为三个分化等级：高分化（well differentiated）、中分化（moderately differentiated）与低分化（poorly differentiated）。据此，本数据集总计包含七个分类类别，可用于分类任务。其中大部分图像的镜检放大倍数为20倍，其余为40倍，该设置充分体现了真实临床实践中常见的组织病理样本的多样性。

搜集汇总

背景与挑战

背景概述

LungHist700是一个包含691张高分辨率肺部组织病理学图像的数据集，涵盖腺癌、鳞状细胞癌和正常肺组织三个主要类别，并细分为七个分类类别（包括不同分化程度）。图像具有20x和40x两种放大倍数，适用于深度学习在肺部病理学中的应用。