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Cancer detection using hyperspectral imaging and evaluation of the superficial tumor margin variance with depth
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Paper Abstract

Head and neck squamous cell carcinoma (SCCa) is primarily managed by surgical resection. Recurrence rates after surgery can be as high as 55% if residual cancer is present. In this study, hyperspectral imaging (HSI) is evaluated for detection of SCCa in ex-vivo surgical specimens. Several methods are investigated, including convolutional neural networks (CNNs) and a spectral-spatial variant of support vector machines. Quantitative results demonstrate that additional processing and unsupervised filtering can improve CNN results to achieve optimal performance. Classifying regions that include specular glare, the average AUC is increased from 0.73 [0.71, 0.75 (95% confidence interval)] to 0.81 [0.80, 0.83] through an unsupervised filtering and majority voting method described. The wavelengths of light used in HSI can penetrate different depths into biological tissue, while the cancer margin may change with depth and create uncertainty in the ground-truth. Through serial histological sectioning, the variance in cancer-margin with depth is also investigated and paired with qualitative classification heat maps using the methods proposed for the testing group SCC patients.

Paper Details

Date Published: 8 March 2019
PDF: 11 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511A (8 March 2019); doi: 10.1117/12.2512985
Show Author Affiliations
Martin Halicek, The Univ. of Texas at Dallas (United States)
Georgia Institute of Technology and Emory Univ. (United States)
Medical College of Georgia, Augusta Univ. (United States)
Himar Fabelo, The Univ. of Texas at Dallas (United States)
Univ. de Las Palmas de Gran Canaria (Spain)
Samuel Ortega, Univ. de Las Palmas de Gran Canaria (Spain)
James V. Little, Emory Univ. School of Medicine (United States)
Xu Wang, Emory Univ. School of Medicine (United States)
Amy Y. Chen, Emory Univ. School of Medicine (United States)
Gustavo Marrero Callico, Univ. de Las Palmas de Gran Canaria (Spain)
Larry L. Myers, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Baran D. Sumer, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Baowei Fei, The Univ. of Texas at Dallas (United States)
The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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