Automatic polyp detection using global geometric constraints and local intensity variation patterns

Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)

Abstract

This paper presents a new method for detecting polyps in colonoscopy. Its novelty lies in integrating the global geometric constraints of polyps with the local patterns of intensity variation across polyp boundaries: the former drives the detector towards the objects with curvy boundaries, while the latter minimizes the misleading effects of polyp-like structures. This paper makes three original contributions: (1) a fast and discriminative patch descriptor for precisely characterizing patterns of intensity variation across boundaries, (2) a new 2-stage classification scheme for accurately excluding non-polyp edges from an overcomplete edge map, and (3) a novel voting scheme for robustly localizing polyps from the retained edges. Evaluations on a public database and our own videos demonstrate that our method is promising and outperforms the state-of-the-art methods.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages179-187
Number of pages9
Volume17
StatePublished - 2014
Externally publishedYes

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Polyps
Politics
Colonoscopy
Databases

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Tajbakhsh, N., Gurudu, S. R., & Liang, J. (2014). Automatic polyp detection using global geometric constraints and local intensity variation patterns. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Vol. 17, pp. 179-187)

Automatic polyp detection using global geometric constraints and local intensity variation patterns. / Tajbakhsh, Nima; Gurudu, Suryakanth R.; Liang, Jianming.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 17 2014. p. 179-187.

Research output: Chapter in Book/Report/Conference proceedingChapter

Tajbakhsh, N, Gurudu, SR & Liang, J 2014, Automatic polyp detection using global geometric constraints and local intensity variation patterns. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. vol. 17, pp. 179-187.
Tajbakhsh N, Gurudu SR, Liang J. Automatic polyp detection using global geometric constraints and local intensity variation patterns. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 17. 2014. p. 179-187
Tajbakhsh, Nima ; Gurudu, Suryakanth R. ; Liang, Jianming. / Automatic polyp detection using global geometric constraints and local intensity variation patterns. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 17 2014. pp. 179-187
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