Linear radial patterns characterization for automatic detection of tonic intestinal contractions

14Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns. © Springer-Verlag Berlin Heidelberg 2006.

References Powered by Scopus

Wireless capsule endoscopy

2747Citations
N/AReaders
Get full text

The Design and Use of Steerable Filters

2514Citations
N/AReaders
Get full text

Fast radial symmetry for detecting points of interest

527Citations
N/AReaders
Get full text

Cited by Powered by Scopus

New Insight Into Intestinal Motor Function via Noninvasive Endoluminal Image Analysis

84Citations
N/AReaders
Get full text

Intestinal motility assessment with video capsule endoscopy: Automatic annotation of phasic intestinal contractions

53Citations
N/AReaders
Get full text

Functional gut disorders or disordered gut function? Small bowel dysmotility evidenced by an original technique

33Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Vilariño, F., Spyridonos, P., Vitrià, J., Malagelada, C., & Radeva, P. (2006). Linear radial patterns characterization for automatic detection of tonic intestinal contractions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4225 LNCS, pp. 178–187). Springer Verlag. https://doi.org/10.1007/11892755_18

Readers' Seniority

Tooltip

Lecturer / Post doc 3

43%

Professor / Associate Prof. 2

29%

PhD / Post grad / Masters / Doc 1

14%

Researcher 1

14%

Readers' Discipline

Tooltip

Computer Science 4

50%

Medicine and Dentistry 2

25%

Engineering 2

25%

Save time finding and organizing research with Mendeley

Sign up for free