Automated detection of Barrett’s esophagus using endoscopic images: a survey

Ghatwary, Noha and Ahmed, Amr and Ye, Xujiong (2017) Automated detection of Barrett’s esophagus using endoscopic images: a survey. In: Medical image understanding and analysis. Communications in Computer and Information Science (723). Springer, pp. 897-908. ISBN UNSPECIFIED

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Abstract

Barrett’s Esophagus (BE) is the predominant sign leading to esophageal adenocarcinoma (EAC) which is cancerous. Esophageal cancer has shown a very low survival rate in the last decade. Early detection of BE, and monitoring cells development is an effective way to control the progression of the cell transform into EAC in the lining of the esophagus. The examination of BE is done by using one the different endoscopy tools, the appearance of endoscopic imaging techniques created the opportunity for computer-aided detection (CAD) systems to develop more frequently. Such methods intend to help physicians by identifying abnormalities more accurately. The purpose of this survey is to discuss advances in the development of BE CAD systems as it has only started to grab attention recently. Starting with a brief introduction about endoscopy modalities used for esophageal examination. Then focusing on detection methods lately developed for BE detection. Remaining challenges are mentioned and some directions for future research are given.

Additional Information:Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11-13, 2017, Proceedings (Communications in Computer and Information Science)
Keywords:Barrett's Esophagus, Computer-Aided Detection (CAD), Endoscopy, Esophageal cancer
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
H Engineering > H130 Computer-Aided Engineering
Divisions:College of Science > School of Computer Science
ID Code:27803
Deposited On:05 Jul 2017 15:12

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