Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

S. Atasoy, D. Mateus, J. Lallemand, A. Meining, G. Z. Yang, N. Navab
Endoscopic Video Manifolds
Medical Image Computing and Computer Assisted Intervention (MICCAI), Beijing, China, September 20-24 2010. (bib)

Postoperative analysis of gastrointestinal (GI) endoscopic videos is a dfficult task because the videos often suffr from a large number of poor-quality frames due to the motion or out-of-focus blur, specular highlights and artefacts caused by turbid uid inside the GI tract. Clinically, each frame of the video is examined individually by the endoscopic expert due to the lack of a suitable visualisation technique. In this work, we introduce a low dimensional representation of endoscopic videos based on a manifold learning approach. The introduced endoscopic video manifolds (EVMs) enable the clustering of poor-quality frames and grouping of different segments of the GI endoscopic video in an unsuper- vised manner to facilitate subsequent visual assessment. In this paper, we present two novel inter-frame similarity measures for manifold learn- ing to create structured manifolds from complex endoscopic videos. Our experiments demonstrate that the proposed method yields high precision and recall values for uninformative frame detection (90:91% and 82:90%) and results in well-structured manifolds for scene clustering.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif