Prospectively collect the hyperspectral image information of ordinary colonoscopic biopsy tissue. The colonoscopic biopsy tissue is from the Endoscopy Center of Qilu Hospital of Shandong University. The hyperspectral images are marked based on the biopsy pathological results, and the deep convolutional neural network (DCNN) model is used. With training and verification, develop the Hyperspectral Imaging Artificial Intelligence Diagnostic System (HSIAIDS) .A portion of colonoscopic biopsy tissue will be collected as a prospective test set to prospectively test the diagnostic performance of the HSIAIDS algorithm.
The purpose of this study is to develop and validate a deep learning algorithm for the diagnosis of colorectal cancer other colorectal disease by marking and analyzing the characteristics of hyperspectral images based on the pathological results of colonoscopic biopsy, so as to improve the objectiveness and intelligence of early colorectal cancer diagnosis.