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Hindi Review Article
Polyp Size Estimation Strategies during Endoscopy Procedures: A Review
Fabio Martínez, Josué Ruano, Martín Gómez and Eduardo Romero*
Computer Imaging and Medical Applications Laboratory, CIM@Lab, Universidad Nacional de Colombia, Colombia, USA
- *Corresponding Author:
- Eduardo Romero
Carrera 30 45-03, Ciudad Universitaria Facultad de Medicina-Edificio 471. Bogotá D.C
Colombia, USA
Tel: +57-1-3165000
Fax: 15025; E-mail: edromero@unal.edu.co
Received date: May 25, 2015 Accepted date: August 12, 2015 Published date: August 18, 2015
Citation: Martínez F, Ruano J, Gómez M, Romero E (2015) Polyp Size Estimation Strategies during Endoscopy Procedures: A Review. J Gastrointest Dig Syst 5:329. doi:10.4172/2161-069X.1000329
Copyright: © 2015 Martínez F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Colorectal cancer is the seventh cause of death and a relevant public health problem. This aggressive cancer is commonly identified during a routine endoscopy examination by characterizing a set of polyps that may appear along the colon and rectum. The polyps are usually described by the tissue appearance, shape, rigidity, surface irregularity, resectability, among others. In particular, the polyp size is an important index since large polyps are labeled as advanced adenomas with strong evidence that such adenomas may turn into cancer. Additionally, this index may also determine the procedure and surgical polyp management because of the bleeding risk. In some protocols, the polyp size indicates a closer surveillance, with additional genetic analyses. Currently, polyp size estimation is a challenge because several limitations such as the endoscopy camera distortions, illumination and exacerbated physiological conditions, abrupt motion and expert subjectivity. This work presents a state-of-the-art review of the current semi-automatic computational approaches for estimating the polyp size, aiming to reduce the subjectivity while exploring the gastrointestinal tract.
