Computational analysis of optical coherence tomography images for the detection of soft tissue sarcomas

Shang Wang, Narendran Sudheendran, Chih Hao Liu, Ravi Kiran Manapuram, Valery P. Zakharov, Davis R. Ingram, Alexander J. Lazar, Dina C. Lev, Raphael E. Pollock, Kirill V. Larin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We present a computational method for the analysis of optical coherence tomography (OCT) images to detect soft tissue sarcomas. The method combines the quantitative analysis of two aspects of information from the intensity A-lines of OCT images; one is the slope of the intensity A-line with dB unit, which is determined by the optical attenuation characteristics of tissue; the other is the standard deviation (SD) of the slope-removed intensity A-line, which is dependent on the tissue structural features. The method is tested with pilot experiments on ex vivo tissue samples of human fat, muscle, well differentiated liposarcoma (WDLS) and leiomyosarcoma. Our results demonstrate the feasibility of this quantitative method in the differentiation of soft tissue sarcomas from normal tissues. This study indicates that OCT can be a potential computer-aided means of automatically and accurately identifying resection margins of soft tissues sarcomas during surgical treatment.

Original languageEnglish
Title of host publicationDynamics and Fluctuations in Biomedical Photonics IX
DOIs
StatePublished - 2013
EventDynamics and Fluctuations in Biomedical Photonics VIII Conference - San Francisco, CA, United States
Duration: 2 Feb 20134 Feb 2013

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8580
ISSN (Print)1605-7422

Conference

ConferenceDynamics and Fluctuations in Biomedical Photonics VIII Conference
Country/TerritoryUnited States
CitySan Francisco, CA
Period2/02/134/02/13

Keywords

  • Image processing
  • Optical coherence tomography
  • Soft tissue sarcoma

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