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Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging.
- Source :
- Journal of Biomedical Optics; Jun2017, Vol. 22 Issue 6, p1-4, 4p
- Publication Year :
- 2017
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10833668
- Volume :
- 22
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Journal of Biomedical Optics
- Publication Type :
- Academic Journal
- Accession number :
- 124244361
- Full Text :
- https://doi.org/10.1117/1.JBO.22.6.060503