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Proceedings Paper

Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images
Author(s): Guolan Lu; Luma Halig; Dongsheng Wang; Zhuo Georgia Chen; Baowei Fei
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Paper Abstract

The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.

Paper Details

Date Published: 12 March 2014
PDF: 8 pages
Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 90360S (12 March 2014); doi: 10.1117/12.2043805
Show Author Affiliations
Guolan Lu, Georgia Institute of Technology (United States)
Emory Univ. (United States)
Luma Halig, 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, Emory Univ. (United States)


Published in SPIE Proceedings Vol. 9036:
Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling
Ziv R. Yaniv; David R. Holmes, Editor(s)

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