Quantitative principal component model for skin chromophore mapping using multi-spectral images and spatial priors

We describe a novel reconstruction algorithm based on Principal Component Analysis (PCA) applied to multi-spectral imaging data. Using numerical phantoms, based on a two layered skin model developed previously, we found analytical expressions, which convert qualitative PCA results into quantitative...

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Detalles Bibliográficos
Autores principales: Kainerstorfer, Jana M., Riley, Jason D., Ehler, Martin, Najafizadeh, Laleh, Amyot, Franck, Hassan, Moinuddin, Pursley, Randall, Demos, Stavros G., Chernomordik, Victor, Pircher, Michael, Smith, Paul D., Hitzenberger, Christoph K., Gandjbakhche, Amir H.
Formato: Texto
Lenguaje:English
Publicado: Optical Society of America 2011
Materias:
Image Reconstruction and Inverse Problems
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3087563/
https://www.ncbi.nlm.nih.gov/pubmed/21559118
http://dx.doi.org/10.1364/BOE.2.001040

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3087563/
https://www.ncbi.nlm.nih.gov/pubmed/21559118
http://dx.doi.org/10.1364/BOE.2.001040

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