ECAT - Endoscopic concept annotation tool

Abstract

The trend to video documentation in minimally invasive surgery demands for effective and expressive semantic content understanding in order to automatically organize huge and rapidly growing endoscopic video archives. To provide such assistance, deep learning proved to be the means of choice, but requires large amounts of high quality training data labeled by domain experts to produce adequate results. We present a web-based annotation system that provides a very efficient workflow for medical domain experts to conveniently create such video training data with minimum effort.