The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Medical hyperspectral imaging: a review
Open accessAbstract
Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.
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Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Siegel, R., Naishadham, D., & Jemal, A. (2012) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20138 · Cited by 10,679
Fisher, B., Anderson, S., Bryant, J., Margolese, R. G., Deutsch, M., Fisher, E. R., Jeong, J.-H., & Wolmark, N. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa022152 · Cited by 6,249
Keshava, N., & Mustard, J. F. (2002) · IEEE Signal Processing Magazine · doi:10.1109/79.974727 · Cited by 2,549
Cited by
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Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2991043 · Cited by 713
Spatial-Spectral Transformer for Hyperspectral Image Classification
He, X., Chen, Y., & Lin, Z. (2021) · Remote Sensing · doi:10.3390/rs13030498 · Cited by 462
A contemporary review of machine learning in otolaryngology–head and neck surgery
Crowson, M. G., Ranisau, J., Eskander, A., Babier, A., Xu, B., Kahmke, R. R., Chen, J. M., & Chan, T. C. Y. (2020) · The Laryngoscope · doi:10.1002/lary.27850 · Cited by 127
Xu, Z., Jiang, Y., Ji, J., Forsberg, E., Li, Y., & He, S. (2020) · Optics Express · doi:10.1364/oe.406036 · Cited by 110
Metadata
- Authors
- Lu, G., & Fei, B.
- Venue
- Journal of Biomedical Optics
- Publisher
- SPIE-Intl Soc Optical Eng
- Published
- 2014-01-20
- Volume
- 19
- Issue
- 1
- Pages
- 010901
- ISSN
- 1083-3668 (ISSN-L)
- OpenAlex
- W1988386267
- Cited by
- 2,291
- References
- 5
- FWCI
- 74.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
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