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Article
Lung cancer diagnosis with quantitative DIC microscopy and support vector machine
International Conference on Innovative Optical Health Science
  • Longfei Zheng
  • Shuangshuang Cai
  • Bixin Zeng
  • Min Xu, Fairfield University
Document Type
Conference Proceeding
Article Version
Publisher's PDF
Publication Date
1-1-2017
Abstract

We report the study of lung squamous cell carcinoma diagnosis using the TI-DIC microscopy and the scattering-phase theorem. The spatially resolved optical properties of tissue are computed from the 2D phase map via the scattering-phase theorem. The scattering coefficient, the reduced scattering coefficient, and the anisotropy factor are all found to increase with the grade of lung cancer. The retrieved optical parameters are shown to distinguish cancer cases from the normal cases with high accuracy. This label-free microscopic approach applicable to fresh tissues may be promising for in situ rapid cancer diagnosis. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Comments

Copyright 2017 Society of Photo Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, or modification of the contents of the publication are prohibited.

The final publisher PDF has been archived here with permission from the copyright holder.

Published Citation
Longfei Zheng, Shuangshuang Cai, Bixin Zeng, Min Xu, "Lung cancer diagnosis with quantitative DIC microscopy and support vector machine", Proc. SPIE 10245, International Conference on Innovative Optical Health Science, 102450K (5 January 2017); doi: 10.1117/12.2268806; https://doi.org/10.1117/12.2268806
DOI
10.1117/12.2268806
None
Peer Reviewed
Citation Information
Longfei Zheng, Shuangshuang Cai, Bixin Zeng and Min Xu. "Lung cancer diagnosis with quantitative DIC microscopy and support vector machine" International Conference on Innovative Optical Health Science Vol. 10245 (2017)
Available at: http://works.bepress.com/min_xu/17/