A learning method for automated polyp detection

Published

Conference Paper

© Springer-Verlag Berlin Heidelberg 2001. Adenomatous polyps in the colon have a high probability of developing into subsequent colorectal carcinoma, the second leading cause of cancer deaths in United States. In this paper, we propose a new method for computer-aided diagnosis of polyps. Initial work with shape detection has shown high sensitivity for polyp detection, but at a cost of too many false positive detections. We present a statistical approach that uses support vector machines to distinguish the differentiating characteristics of polyps and healthy tissue, and subsequently uses this information for the classification of the new cases. One of the main contributions of the paper is a new 3-D pattern analysis approach, which combines the information from many random images to generate reliable signatures of the shapes. At 80% polyp detection rate, the proposed system reduces the false positive rate by 80% compared to previous work.

Full Text

Duke Authors

Cited Authors

  • Gokturk, SB; Tomasi, C; Acar, B; Paik, D; Beaulieu, C; Napel, S

Published Date

  • January 1, 2001

Published In

Volume / Issue

  • 2208 /

Start / End Page

  • 85 - 93

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 10 (ISBN-10)

  • 3540426973

International Standard Book Number 13 (ISBN-13)

  • 9783540454687

Digital Object Identifier (DOI)

  • 10.1007/3-540-45468-3_11

Citation Source

  • Scopus