@inproceedings{67477f24c88242c592c221568ba6e275,
title = "A dual stream network for tumor detection in hyperspectral images",
abstract = "Hyperspectral imaging has become an emerging imaging modality for medical applications. In this work, we propose to combine both the spectral and structural information in the hyperspectral data cube for tumor detection in tongue tissue. A dual stream network is designed, with a spectral and a structural branch. Hyperspectral data (480 to 920 nm) is collected from 7 patients with tongue squamous cell carcinoma. Histopathological analysis provided ground truth labels. The proposed dual stream model outperforms the pure spectral and structural approaches with areas under the ROC-curve of 0.90, 0.87 and 0.85, respectively.",
keywords = "Hyperspectral imaging, Machine learning, Neural networks, Tongue tumor",
author = "Weijtmans, {P. J.C.} and C. Shan and T. Tan and {Brouwer De Koning}, {S. G.} and Ruers, {T. J.M.}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 ; Conference date: 08-04-2019 Through 11-04-2019",
year = "2019",
month = apr,
doi = "10.1109/ISBI.2019.8759566",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "1256--1259",
booktitle = "ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging",
address = "United States",
}