English

Automatic View-Point Selection for Inter-Operative Endoscopic Surveillance

Computer Vision and Pattern Recognition 2016-10-14 v1

Abstract

Esophageal adenocarcinoma arises from Barrett's esophagus, which is the most serious complication of gastroesophageal reflux disease. Strategies for screening involve periodic surveillance and tissue biopsies. A major challenge in such regular examinations is to record and track the disease evolution and re-localization of biopsied sites to provide targeted treatments. In this paper, we extend our original inter-operative relocalization framework to provide a constrained image based search for obtaining the best view-point match to the live view. Within this context we investigate the effect of: the choice of feature descriptors and color-space; filtering of uninformative frames and endoscopic modality, for view-point localization. Our experiments indicate an improvement in the best view-point retrieval rate to [92%,87%] from [73%,76%] (in our previous approach) for NBI and WL.

Keywords

Cite

@article{arxiv.1610.04097,
  title  = {Automatic View-Point Selection for Inter-Operative Endoscopic Surveillance},
  author = {Anant S. Vemuri and Stephane A. Nicolau and Jacques Marescaux and Luc Soler and Nicholas Ayache},
  journal= {arXiv preprint arXiv:1610.04097},
  year   = {2016}
}

Comments

Medical Content-based Retrieval for Clinical Decision Support and Treatment Planning, MICCAI Conference

R2 v1 2026-06-22T16:19:50.749Z