Literature DB >> 16293240

An intelligent system for automatic detection of gastrointestinal adenomas in video endoscopy.

Dimitris K Iakovidis1, Dimitris E Maroulis, Stavros A Karkanis.   

Abstract

Today 95% of all gastrointestinal carcinomas are believed to arise from adenomas. The early detection of adenomas could prevent their evolution to cancer. A novel system for the support of the detection of adenomas in gastrointestinal video endoscopy is presented. Unlike other systems, it accepts standard low-resolution video input thus requiring less computational resources and facilitating both portability and the potential to be used in telemedicine applications. It combines intelligent processing techniques of SVMs and color-texture analysis methodologies into a sound pattern recognition framework. Concerning the system's accuracy this was measured using ROC analysis and found to exceed 94%.

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Year:  2005        PMID: 16293240     DOI: 10.1016/j.compbiomed.2005.09.008

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  12 in total

1.  Recent advances in targeted endoscopic imaging: Early detection of gastrointestinal neoplasms.

Authors:  Yong-Soo Kwon; Young-Seok Cho; Tae-Jong Yoon; Ho-Shik Kim; Myung-Gyu Choi
Journal:  World J Gastrointest Endosc       Date:  2012-03-16

2.  A novel summary report of colonoscopy: timeline visualization providing meaningful colonoscopy video information.

Authors:  Minwoo Cho; Jee Hyun Kim; Hyoun Joong Kong; Kyoung Sup Hong; Sungwan Kim
Journal:  Int J Colorectal Dis       Date:  2018-03-08       Impact factor: 2.571

Review 3.  Scoping out the future: The application of artificial intelligence to gastrointestinal endoscopy.

Authors:  Scott B Minchenberg; Trent Walradt; Jeremy R Glissen Brown
Journal:  World J Gastrointest Oncol       Date:  2022-05-15

Review 4.  Artificial Intelligence and Polyp Detection.

Authors:  Nicholas Hoerter; Seth A Gross; Peter S Liang
Journal:  Curr Treat Options Gastroenterol       Date:  2020-01-21

5.  Delaunay triangulation-based pit density estimation for the classification of polyps in high-magnification chromo-colonoscopy.

Authors:  M Häfner; M Liedlgruber; A Uhl; A Vécsei; F Wrba
Journal:  Comput Methods Programs Biomed       Date:  2012-02-10       Impact factor: 5.428

6.  Color treatment in endoscopic image classification using multi-scale local color vector patterns.

Authors:  M Häfner; M Liedlgruber; A Uhl; A Vécsei; F Wrba
Journal:  Med Image Anal       Date:  2011-05-17       Impact factor: 8.545

7.  Looking forwards: not necessarily the best in capsule endoscopy?

Authors:  Anastasios Koulaouzidis; Konstantinos J Dabos
Journal:  Ann Gastroenterol       Date:  2013

8.  The Argos project: The development of a computer-aided detection system to improve detection of Barrett's neoplasia on white light endoscopy.

Authors:  Jeroen de Groof; Fons van der Sommen; Joost van der Putten; Maarten R Struyvenberg; Sveta Zinger; Wouter L Curvers; Oliver Pech; Alexander Meining; Horst Neuhaus; Raf Bisschops; Erik J Schoon; Peter H de With; Jacques J Bergman
Journal:  United European Gastroenterol J       Date:  2019-03-06       Impact factor: 4.623

9.  An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features.

Authors:  Mustain Billah; Sajjad Waheed; Mohammad Motiur Rahman
Journal:  Int J Biomed Imaging       Date:  2017-08-14

Review 10.  Artificial intelligence in gastrointestinal endoscopy: The future is almost here.

Authors:  Muthuraman Alagappan; Jeremy R Glissen Brown; Yuichi Mori; Tyler M Berzin
Journal:  World J Gastrointest Endosc       Date:  2018-10-16
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