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Proceedings Paper

Hyperspectral imaging for detection of breast cancer in resection margins using spectral-spatial classification (Conference Presentation)

Paper Abstract

The lack of sufficient margin assessment during breast conserving surgery results in up to 40% of the cases in incomplete tumor removal. We evaluate the feasibility of hyperspectral imaging as an intra-operative margin assessment technique. Hyperspectral imaging rapidly collects diffuse reflected light with a large field of view over a broad wavelength range (900-1700 nm). Thereby a 3D hypercube is created that contains both spectral and spatial information of the imaged scene. Measurements are performed on 20 freshly excised breast specimen with a pushbroom camera (900-1700 nm). The specimen is sliced according to standard protocol and one slice, that contains both tumour and healthy tissue, is selected for optical measurements. Histopathology of the measured surface of this slice is obtained afterwards and used for hyperspectral data labelling. We use a spectral-spatial classifier to discriminate tumorous tissue from surrounding healthy tissue. First, we apply a linear Support Vector Machine (SVM) to obtain a pixel-based spectral classification. As output, we obtain classified pixels and their probability estimates. Second, we use this output as input for the spatial regulation, which is based on Markov Random Fields. This results in a spectral-spatial classification accuracy of 91%. Spatial regulation mainly affects pixels with a tissue type classification dissimilar to its neighbourhood. Thereby, the spectral classification accuracy is not significantly increased but the ‘pepper-and-salt’ effect, observed after pixel-based classification, is reduced.

Paper Details

Date Published: 14 March 2018
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Proc. SPIE 10472, Diagnosis and Treatment of Diseases in the Breast and Reproductive System IV, 104720F (14 March 2018); doi: 10.1117/12.2288367
Show Author Affiliations
Esther Kho, The Netherlands Cancer Institute (Netherlands)
Lisanne L. de Boer, The Netherlands Cancer Institute (Netherlands)
Koen K. Van de Vijver, The Netherlands Cancer Institute (Netherlands)
Henricus J. C. M. Sterenborg, The Netherlands Cancer Institute (Netherlands)
Academisch Medisch Centrum (Netherlands)
Theo J.M. Ruers, The Netherlands Cancer Institute (Netherlands)
MIRA Institute, Univ. Twente (Netherlands)


Published in SPIE Proceedings Vol. 10472:
Diagnosis and Treatment of Diseases in the Breast and Reproductive System IV
Melissa C. Skala; Paul J. Campagnola, Editor(s)

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