Unsupervised colonoscopic depth estimation by domain translations with a Lambertian-reflection keeping auxiliary task.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
May 17, 2021
Abstract
PURPOSE: A three-dimensional (3D) structure extraction technique viewed from a two-dimensional image is essential for the development of a computer-aided diagnosis (CAD) system for colonoscopy. However, a straightforward application of existing depth-estimation methods to colonoscopic images is impossible or inappropriate due to several limitations of colonoscopes. In particular, the absence of ground-truth depth for colonoscopic images hinders the application of supervised machine learning methods. To circumvent these difficulties, we developed an unsupervised and accurate depth-estimation method.