Homology-Based Image Processing for Automatic Classification of Histopathological Images of Lung Tissue.

ABSTRACT: The purpose of this study was to develop a computer-aided diagnosis (CAD) system for automatic classification of histopathological images of lung tissues. Two datasets (private and public datasets) were obtained and used for developing and validating CAD. The private dataset consists of 94 histopathological images that were obtained for the following five categories: normal, emphysema, atypical adenomatous hyperplasia, lepidic pattern of adenocarcinoma, and invasive adenocarcinoma. The public dataset consists of 15,000 histopathological images that were obtained for the following three categories: lung adenocarcinoma, lung squamous cell carcinoma, and benign lung tissue. These images were automatically classified using machine learning and two types of image feature extraction: conventiona

SUBMITTER: Nishio M 

PROVIDER: S-EPMC8001245 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature