Literature DB >> 22273792

Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review.

Michael Liedlgruber1, Andreas Uhl.   

Abstract

Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the human body. The advent of endoscopic imaging techniques-allowing the acquisition of images or videos-created the possibility for the development of the whole new branch of computer-aided decision support systems. Such systems aim at helping physicians to identify possibly malignant abnormalities more accurately. At the beginning of this paper, we give a brief introduction to the history of endoscopy, followed by introducing the main types of endoscopes which emerged so far (flexible endoscope, wireless capsule endoscope, and confocal laser endomicroscope). We then give a brief introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract. Then we present general facts and figures concerning computer-aided decision support systems and summarize work specifically targeted at computer-aided decision support in the gastrointestinal tract. This summary is followed by a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.

Entities:  

Mesh:

Year:  2011        PMID: 22273792     DOI: 10.1109/RBME.2011.2175445

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  21 in total

Review 1.  Software for enhanced video capsule endoscopy: challenges for essential progress.

Authors:  Dimitris K Iakovidis; Anastasios Koulaouzidis
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2015-02-17       Impact factor: 46.802

2.  A Novel Endoscope System for Position Detection and Depth Estimation of the Ureter.

Authors:  Enmin Song; Feng Yu; Hong Liu; Ning Cheng; Yunlong Li; Lianghai Jin; Chih-Cheng Hung
Journal:  J Med Syst       Date:  2016-10-11       Impact factor: 4.460

3.  Three-dimensional image reconstruction in capsule endoscopy.

Authors:  Anastasios Koulaouzidis; Alexandros Karargyris
Journal:  World J Gastroenterol       Date:  2012-08-21       Impact factor: 5.742

4.  Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis.

Authors:  Michael Gadermayr; Hubert Kogler; Maximilian Karla; Dorit Merhof; Andreas Uhl; Andreas Vécsei
Journal:  World J Gastroenterol       Date:  2016-08-21       Impact factor: 5.742

5.  In-vivo Barrett's esophagus digital pathology stage classification through feature enhancement of confocal laser endomicroscopy.

Authors:  Noha Ghatwary; Amr Ahmed; Enrico Grisan; Hamid Jalab; Luc Bidaut; Xujiong Ye
Journal:  J Med Imaging (Bellingham)       Date:  2019-03-05

6.  Annotating Early Esophageal Cancers Based on Two Saliency Levels of Gastroscopic Images.

Authors:  Dingyun Liu; Nini Rao; Xinming Mei; Hongxiu Jiang; Quanchi Li; ChengSi Luo; Qian Li; Chengshi Zeng; Bing Zeng; Tao Gan
Journal:  J Med Syst       Date:  2018-10-16       Impact factor: 4.460

7.  Use of adaptive hybrid filtering process in Crohn's disease lesion detection from real capsule endoscopy videos.

Authors:  Vasileios S Charisis; Leontios J Hadjileontiadis
Journal:  Healthc Technol Lett       Date:  2016-03-21

Review 8.  Gastrointestinal diagnosis using non-white light imaging capsule endoscopy.

Authors:  Gerard Cummins; Benjamin F Cox; Gastone Ciuti; Thineskrishna Anbarasan; Marc P Y Desmulliez; Sandy Cochran; Robert Steele; John N Plevris; Anastasios Koulaouzidis
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2019-07       Impact factor: 46.802

9.  A Gratifying Step forward for the Application of Artificial Intelligence in the Field of Endoscopy: A Narrative Review.

Authors:  Yixin Xu; Yulin Tan; Yibo Wang; Jie Gao; Dapeng Wu; Xuezhong Xu
Journal:  Surg Laparosc Endosc Percutan Tech       Date:  2020-10-28       Impact factor: 1.719

Review 10.  Application of Artificial Intelligence in the Detection and Characterization of Colorectal Neoplasm.

Authors:  Kyeong Ok Kim; Eun Young Kim
Journal:  Gut Liver       Date:  2021-05-15       Impact factor: 4.519

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