title: Three-dimensional reconstruction of the digestive wall in capsule endoscopy videos using elastic video interpolation.
abstract: Wireless capsule endoscopy is a revolutionary technology that allows physicians to examine the digestive tract of a human body in the minimum invasive way. Physicians can detect diseases such as blood-based abnormalities, polyps, ulcers, and Crohn's disease. Although this technology is really a marvel of our modern times, currently it suffers from two serious drawbacks: 1) frame rate is low (3 frames/s) and 2) no 3-D representation of the objects is captured from the camera of the capsule. In this paper we offer solutions (methodologies) that deal with each of the above issues improving the current technology without forcing hardware upgrades. These methodologies work synergistically to create smooth and visually friendly interpolated images from consecutive frames, while preserving the structure of the observed objects. They also extract and represent the texture of the surface of the digestive tract in 3-D. Thus the purpose of our methodology is not to reduce the time that the gastroenterologists need to spend to examine the video. On the contrary, the purpose is to enhance the video and therefore improve the viewing of the digestive tract leading to a more qualitative and efficient examination. The proposed work introduces 3-D capsule endoscopy textured results that have been welcomed by Digestive Specialists, Inc., Dayton, OH. Finally, illustrative results are given at the end of the paper.
authors.affiliation: College of Engineering, Assistive Technologies Research Center, Wright State University, Dayton, OH 45435, USA. karargyris@gmail.com
authors.forename: Alexandros
authors.initials: A
authors.lastname: Karargyris
authors.forename: Nikolaos
authors.initials: N
authors.lastname: Bourbakis
mesh_terms: D000465:Algorithms; D053704:Capsule Endoscopy / Q000379:methods*; D041981:Gastrointestinal Tract / Q000033:anatomy & histology* / Q000473:pathology / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010528:Peristalsis