Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.
Journal:
Computational and mathematical methods in medicine
Published Date:
Jan 1, 2020
Abstract
METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing colonoscopy. The convolutional neural network model is used to detect whether the image contains lesions: CRC, colorectal adenoma (CRA), and colorectal polyps. The accuracy, sensitivity, and specificity rates are used as indicators to evaluate the model. Then, the instance segmentation model is used to locate and classify the lesions on the images containing lesions, and mAP (mean average precision), AP, and AP are used to evaluate the performance of an instance segmentation model.