A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist searches for polyps.

Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists.

Background: Machine learning, especially deep learning, is becoming more and more relevant in research and development in the medical domain. For all the supervised deep learning applications, data is the most critical factor in securing successful implementation and sustaining the progress of the machine learning model. Especially gastroenterological data, which often involves endoscopic videos, are cumbersome to annotate.

Semi-Automated Machine Learning Video Annotation for Gastroenterologists.

A semi-automatic tool for fast and accurate annotation of endoscopic videos utilizing trained object detection models is presented. A novel workflow is implemented and the preliminary results suggest that the annotation process is nearly twice as fast with our novel tool compared to the current state of the art.