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Proceedings Paper

Tumor margin classification of head and neck cancer using hyperspectral imaging and convolutional neural networks
Author(s): Martin Halicek; James V. Little; Xu Wang; Mihir Patel; Christopher C. Griffith; Amy Y. Chen; Baowei Fei
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Paper Abstract

One of the largest factors affecting disease recurrence after surgical cancer resection is negative surgical margins. Hyperspectral imaging (HSI) is an optical imaging technique with potential to serve as a computer aided diagnostic tool for identifying cancer in gross ex-vivo specimens. We developed a tissue classifier using three distinct convolutional neural network (CNN) architectures on HSI data to investigate the ability to classify the cancer margins from ex-vivo human surgical specimens, collected from 20 patients undergoing surgical cancer resection as a preliminary validation group. A new approach for generating the HSI ground truth using a registered histological cancer margin is applied in order to create a validation dataset. The CNN-based method classifies the tumor-normal margin of squamous cell carcinoma (SCCa) versus normal oral tissue with an area under the curve (AUC) of 0.86 for inter-patient validation, performing with 81% accuracy, 84% sensitivity, and 77% specificity. Thyroid carcinoma cancer-normal margins are classified with an AUC of 0.94 for inter-patient validation, performing with 90% accuracy, 91% sensitivity, and 88% specificity. Our preliminary results on a limited patient dataset demonstrate the predictive ability of HSI-based cancer margin detection, which warrants further investigation with more patient data and additional processing techniques to optimize the proposed deep learning method.

Paper Details

Date Published: 12 March 2018
PDF: 11 pages
Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 1057605 (12 March 2018); doi: 10.1117/12.2293167
Show Author Affiliations
Martin Halicek, Georgia Institute of Technology & Emory Univ. (United States)
Augusta Univ. (United States)
James V. Little, Emory Univ. School of Medicine (United States)
Xu Wang, Emory Univ. School of Medicine (United States)
Mihir Patel, Emory Univ. School of Medicine (United States)
The Winship Cancer Institute of Emory Univ. (United States)
Christopher C. Griffith, Emory Univ. School of Medicine (United States)
Amy Y. Chen, Emory Univ. School of Medicine (United States)
The Winship Cancer Institute of Emory Univ. (United States)
Baowei Fei, Georgia Institute of Technology & Emory Univ. (United States)
The Winship Cancer Institute of Emory Univ. (United States)
Emory Univ. (United States)


Published in SPIE Proceedings Vol. 10576:
Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Robert J. Webster, Editor(s)

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