Options
2021
Conference Paper
Title
A Geometric and Textural Model of the Colon as Ground Truth for Deep Learning-based 3D-reconstruction
Abstract
For endoscopic examinations of the large intestine, the limited field of vision related to the keyhole view of the endoscope can be a problem. A panoramic view of the video images acquired during a colonoscopy can potentially enlarge the field of view in real-time and may ensure that the performing physician has examined the entire organ. To train and test such a panorama-generation system, endoscopic video sequences with information about the geometry are necessary, but rarely exist. Therefore, we created a virtual phantom of the colon with a 3D-modelling software and propose different methods for realistic-looking textures. This allows us to perform a ""virtual colonoscopy"" and provide a well-defined test environment as well as supplement our training data for deep learning.