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Proceedings Paper

Quantitative wavelength analysis and image classification for intraoperative cancer diagnosis with hyperspectral imaging
Author(s): Guolan Lu; Xulei Qin; Dongsheng Wang; Zhuo Georgia Chen; Baowei Fei
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Paper Abstract

Complete surgical removal of tumor tissue is essential for postoperative prognosis after surgery. Intraoperative tumor imaging and visualization are an important step in aiding surgeons to evaluate and resect tumor tissue in real time, thus enabling more complete resection of diseased tissue and better conservation of healthy tissue. As an emerging modality, hyperspectral imaging (HSI) holds great potential for comprehensive and objective intraoperative cancer assessment. In this paper, we explored the possibility of intraoperative tumor detection and visualization during surgery using HSI in the wavelength range of 450 nm - 900 nm in an animal experiment. We proposed a new algorithm for glare removal and cancer detection on surgical hyperspectral images, and detected the tumor margins in five mice with an average sensitivity and specificity of 94.4% and 98.3%, respectively. The hyperspectral imaging and quantification method have the potential to provide an innovative tool for image-guided surgery.

Paper Details

Date Published: 18 March 2015
PDF: 10 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94151B (18 March 2015); doi: 10.1117/12.2082284
Show Author Affiliations
Guolan Lu, Georgia Institute of Technology (United States)
Emory Univ. (United States)
Xulei Qin, Emory Univ. (United States)
Dongsheng Wang, Emory Univ. (United States)
Zhuo Georgia Chen, Emory Univ. (United States)
Baowei Fei, Georgia Institute of Technology (United States)
Emory Univ. (United States)
Winship Cancer Institute of Emory Univ. (United States)


Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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