TY - JOUR
T1 - Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging
AU - Halicek, Martin
AU - Lu, Guolan
AU - Little, James V.
AU - Wang, Xu
AU - Patel, Mihir
AU - Griffith, Christopher C.
AU - El-Deiry, Mark W.
AU - Chen, Amy Y.
AU - Fei, Baowei
N1 - Publisher Copyright:
© The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including.
PY - 2017/6/1
Y1 - 2017/6/1
N2 - Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI. The CNN classification was validated by the manual annotation of a pathologist specialized in head and neck cancer. The preliminary results of 50 patients indicate the potential of HSI and deep learning for automatic tissue-labeling of surgical specimens of head and neck patients.
AB - Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI. The CNN classification was validated by the manual annotation of a pathologist specialized in head and neck cancer. The preliminary results of 50 patients indicate the potential of HSI and deep learning for automatic tissue-labeling of surgical specimens of head and neck patients.
KW - Cancer detection
KW - Convolutional neural network
KW - Deep learning
KW - Hyperspectral imaging
KW - Image-guided surgery
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U2 - 10.1117/1.JBO.22.6.060503
DO - 10.1117/1.JBO.22.6.060503
M3 - Article
C2 - 28655055
AN - SCOPUS:85021747853
SN - 1083-3668
VL - 22
JO - Journal of Biomedical Optics
JF - Journal of Biomedical Optics
IS - 6
M1 - 060503
ER -