A clinically viable Capsule Endoscopy video analysis platform for automatic bleeding detection

Steven Yi, Heng Jiao, Jean Xie, Peter Mui, Jonathan A Leighton, Shabana F Pasha, Lauri Rentz, Mahmood Abedi

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

1 Scopus citations

Abstract

In this paper, we present a novel and clinically valuable software platform for automatic bleeding detection on gastrointestinal (GI) tract from Capsule Endoscopy (CE) videos. Typical CE videos for GI tract run about 8 hours and are manually reviewed by physicians to locate diseases such as bleedings and polyps. As a result, the process is time consuming and is prone to disease miss-finding. While researchers have made efforts to automate this process, however, no clinically acceptable software is available on the marketplace today. Working with our collaborators, we have developed a clinically viable software platform called GISentinel for fully automated GI tract bleeding detection and classification. Major functional modules of the SW include: the innovative graph based NCut segmentation algorithm, the unique feature selection and validation method (e.g. illumination invariant features, color independent features, and symmetrical texture features), and the cascade SVM classification for handling various GI tract scenes (e.g. normal tissue, food particles, bubbles, fluid, and specular reflection). Initial evaluation results on the SW have shown zero bleeding instance miss-finding rate and 4.03% false alarm rate. This work is part of our innovative 2D/3D based GI tract disease detection software platform. While the overall SW framework is designed for intelligent finding and classification of major GI tract diseases such as bleeding, ulcer, and polyp from the CE videos, this paper will focus on the automatic bleeding detection functional module.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume8670
DOIs
StatePublished - 2013
EventMedical Imaging 2013: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: Feb 12 2013Feb 14 2013

Other

OtherMedical Imaging 2013: Computer-Aided Diagnosis
CountryUnited States
CityLake Buena Vista, FL
Period2/12/132/14/13

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Keywords

  • And false alarm
  • Automatic bleeding detection
  • Bleeding classification
  • Capsule Endoscopy
  • CE imaging
  • Disease detection
  • Miss-detection

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Yi, S., Jiao, H., Xie, J., Mui, P., Leighton, J. A., Pasha, S. F., Rentz, L., & Abedi, M. (2013). A clinically viable Capsule Endoscopy video analysis platform for automatic bleeding detection. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 8670). [867028] https://doi.org/10.1117/12.2001881