A dual stream network for tumor detection in hyperspectral images

P.J.C. Weijtmans; C. Shan; T. Tan; S.G. Brouwer de Koning; T.J.M. Ruers

doi:10.1109/ISBI.2019.8759566

A dual stream network for tumor detection in hyperspectral images

P.J.C. Weijtmans, C. Shan, T. Tan, S.G. Brouwer de Koning, T.J.M. Ruers

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

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.

Original language	English
Title of host publication	ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
Place of Publication	Piscataway
Publisher	IEEE Computer Society
Pages	1256-1259
Number of pages	4
ISBN (Electronic)	9781538636411
DOIs	https://doi.org/10.1109/ISBI.2019.8759566
Publication status	Published - 1 Apr 2019
Event	16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy Duration: 8 Apr 2019 → 11 Apr 2019

Conference

Conference	16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
Abbreviated title	ISBI 2019
Country	Italy
City	Venice
Period	8/04/19 → 11/04/19

Keywords

Hyperspectral imaging
Machine learning
Neural networks
Tongue tumor

Access to Document

10.1109/ISBI.2019.8759566

Link to publication in Scopus

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Cite this

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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",

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Weijtmans, PJC, Shan, C, Tan, T, Brouwer de Koning, SG & Ruers, TJM 2019, A dual stream network for tumor detection in hyperspectral images. in ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging., 8759566, IEEE Computer Society, Piscataway, pp. 1256-1259, 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019, Venice, Italy, 8/04/19. https://doi.org/10.1109/ISBI.2019.8759566

A dual stream network for tumor detection in hyperspectral images. / Weijtmans, P.J.C.; Shan, C.; Tan, T.; Brouwer de Koning, S.G.; Ruers, T.J.M.

ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. Piscataway : IEEE Computer Society, 2019. p. 1256-1259 8759566.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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