Principal component model of multispectral data for near real-time skin chromophore mapping

Jana M. Kainerstorfer, Martin Ehler, Franck Amyot, Moinuddin Hassan, Stavros G. Demos, Victor Chernomordik, Christoph K. Hitzenberger, Amir H. Gandjbakhche, Jason D. Riley

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Abstract. Multispectral images of skin contain information on the spatial distribution of biological chromophores, such as blood and melanin. From this, parameters such as blood volume and blood oxygenation can be retrieved using reconstruction algorithms. Most such approaches use some form of pixelwise or volumetric reconstruction code. We explore the use of principal component analysis (PCA) of multispectral images to access blood volume and blood oxygenation in near real time. We present data from healthy volunteers under arterial occlusion of the forearm, experiencing ischemia and reactive hyperemia. Using a two-layered analytical skin model, we show reconstruction results of blood volume and oxygenation and compare it to the results obtained from our new spectral analysis based on PCA. We demonstrate that PCA applied to multispectral images gives near equivalent results for skin chromophore mapping and quantification with the advantage of being three orders of magnitude faster than the reconstruction algorithm.

Original languageEnglish (US)
Article number046007
JournalJournal of Biomedical Optics
Issue number4
StatePublished - Jul 2010
Externally publishedYes


  • Biophotonics
  • Blood volume
  • Modeling
  • Multispectral imaging
  • Principal component analysis
  • Tissue oxygenation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials
  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics


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