A classification-enhanced vote accumulation scheme for detecting colonic polyps

Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    19 Scopus citations

    Abstract

    Colorectal cancer most often begins as abnormal growth of the colon wall, commonly referred to as polyps. It has been shown that the timely removal of polyps with optical colonoscopy (OC) significantly reduces the incidence and mortality of colorectal cancer. However, a significant number of polyps are missed during OC in clinical practice - the pooled miss-rate for all polyps is 22% (95% CI, 19%-26%). Computer-aided detection may offer promises of reducing polyp miss-rate. This paper proposes a new automatic polyp detection method. Given a colonoscopy image, the main idea is to identify the edge pixels that lie on the boundary of polyps and then determine the location of a polyp from the identified edges. To do so, we first use the Canny edge detector to form a crude set of edge pixels, and then apply a set of boundary classifiers to remove a large portion of irrelevant edges. The polyp locations are then determined by a novel vote accumulation scheme that operates on the positively classified edge pixels. We evaluate our method on 300 images from a publicly available database and obtain results superior to the state-of-the-art performance.

    Original languageEnglish (US)
    Title of host publicationAbdominal Imaging
    Subtitle of host publicationComputation and Clinical Applications - 5th International Workshop, Held in Conjunction with MICCAI 2013, Proceedings
    Pages53-62
    Number of pages10
    DOIs
    StatePublished - Oct 31 2013
    Event5th International Workshop on Abdominal Imaging: Computation and Clinical Applications, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - Nagoya, Japan
    Duration: Sep 22 2013Sep 22 2013

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume8198 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other5th International Workshop on Abdominal Imaging: Computation and Clinical Applications, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013
    CountryJapan
    CityNagoya
    Period9/22/139/22/13

    Keywords

    • Optical colonoscopy
    • boundary classification
    • polyp detection
    • random forest
    • voting scheme

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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  • Cite this

    Tajbakhsh, N., Gurudu, S. R., & Liang, J. (2013). A classification-enhanced vote accumulation scheme for detecting colonic polyps. In Abdominal Imaging: Computation and Clinical Applications - 5th International Workshop, Held in Conjunction with MICCAI 2013, Proceedings (pp. 53-62). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8198 LNCS). https://doi.org/10.1007/978-3-642-41083-3_7