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A complete system for candidate polyps detection in virtual colonoscopy

Publication ,  Journal Article
Fiori, M; Musé, P; Sapiro, G
Published in: International Journal of Pattern Recognition and Artificial Intelligence
January 1, 2014

We present a computer-aided detection pipeline for polyp detection in Computer tomographic colonography. The first stage of the pipeline consists of a simple colon segmentation technique that enhances polyps, which is followed by an adaptive-scale candidate polyp delineation, in order to capture the appropriate polyp size. In the last step, candidates are classified based on new texture and geometric features that consider both the information in the candidate polyp location and its immediate surrounding area. The system is tested with ground truth data, including flat and small polyps which are hard to detect even with optical colonoscopy. We achieve 100% sensitivity for polyps larger than 6mm in size with just 0.9 false positives per case, and 93% sensitivity with 2.8 false positives per case for polyps larger than 3mm in size.

Duke Scholars

Published In

International Journal of Pattern Recognition and Artificial Intelligence

DOI

ISSN

0218-0014

Publication Date

January 1, 2014

Volume

28

Issue

7

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4603 Computer vision and multimedia computation
  • 4602 Artificial intelligence
  • 1702 Cognitive Sciences
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Fiori, M., Musé, P., & Sapiro, G. (2014). A complete system for candidate polyps detection in virtual colonoscopy. International Journal of Pattern Recognition and Artificial Intelligence, 28(7). https://doi.org/10.1142/S0218001414600143
Fiori, M., P. Musé, and G. Sapiro. “A complete system for candidate polyps detection in virtual colonoscopy.” International Journal of Pattern Recognition and Artificial Intelligence 28, no. 7 (January 1, 2014). https://doi.org/10.1142/S0218001414600143.
Fiori M, Musé P, Sapiro G. A complete system for candidate polyps detection in virtual colonoscopy. International Journal of Pattern Recognition and Artificial Intelligence. 2014 Jan 1;28(7).
Fiori, M., et al. “A complete system for candidate polyps detection in virtual colonoscopy.” International Journal of Pattern Recognition and Artificial Intelligence, vol. 28, no. 7, Jan. 2014. Scopus, doi:10.1142/S0218001414600143.
Fiori M, Musé P, Sapiro G. A complete system for candidate polyps detection in virtual colonoscopy. International Journal of Pattern Recognition and Artificial Intelligence. 2014 Jan 1;28(7).
Journal cover image

Published In

International Journal of Pattern Recognition and Artificial Intelligence

DOI

ISSN

0218-0014

Publication Date

January 1, 2014

Volume

28

Issue

7

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4603 Computer vision and multimedia computation
  • 4602 Artificial intelligence
  • 1702 Cognitive Sciences
  • 0801 Artificial Intelligence and Image Processing