title: Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections.
abstract: Recently, hyperspectral imaging (HSI) systems, which can provide 100 or more wavelengths of emission autofluorescence measures, have been used to delineate more complete spectral patterns associated with certain molecules relevant to cancerization. Such a spectral fingerprint may reliably correspond to a certain type of molecule and thus can be treated as a biomarker for the presence of that molecule. However, the outcomes of HSI systems can be a complex mixture of characteristic spectra of a variety of molecules as well as optical interferences due to reflection, scattering, and refraction. As a result, the mixed nature of raw HSI data might obscure the extraction of consistent spectral fingerprints. Here we present the extraction of the characteristic spectra associated with keratinized tissues from the HSI data of tissue sections from 30 oral cancer patients (31 tissue samples in total), excited at two different wavelength ranges (330 to 385 and 470 to 490 nm), using independent and principal component analysis (ICA and PCA) methods. The results showed that for both excitation wavelength ranges, ICA was able to resolve much more reliable spectral fingerprints associated with the keratinized tissues for all the oral cancer tissue sections with significantly higher mean correlation coefficients as compared to PCA (p<0.001).
authors.affiliation: China Medical University, Graduate Institute of Clinical Medical Science, Taichung, Taiwan 404bChina Medical University, Biomedical Engineering Research and Development Center, Taichung, Taiwan 404cUniversity of California San Diego, Institute for Neural Computation, La Jolla 92093.
authors.forename: Jeng-Ren
authors.initials: JR
authors.lastname: Duann
authors.affiliation: National Yang-Ming University, Department of Dentistry, Taipei, Taiwan 112, New ZealandeChina Medical University and Hospital, Department of Pathology, Taichung, Taiwan 404fChina Medical University and Beigang Hospital, Department of Pathology, Yunlin, Taiwan 651.
authors.forename: Chia-Ing
authors.initials: CI
authors.lastname: Jan
authors.affiliation: National Chiao Tung University, Department of Electrical Engineering, Hsinchu, Taiwan 300.
authors.forename: Mang
authors.initials: M
authors.lastname: Ou-Yang
authors.affiliation: China Medical University, Biomedical Engineering Research and Development Center, Taichung, Taiwan 404hDepartment of Otolaryngology, China Medical University, Taichung, Taiwan 404.
authors.forename: Chia-Yi
authors.initials: CY
authors.lastname: Lin
authors.affiliation: China Medical University, Biomedical Engineering Research and Development Center, Taichung, Taiwan 404.
authors.forename: Jen-Feng
authors.initials: JF
authors.lastname: Mo
authors.affiliation: China Medical University, Biomedical Engineering Research and Development Center, Taichung, Taiwan 404.
authors.forename: Yung-Jiun
authors.initials: YJ
authors.lastname: Lin
authors.affiliation: Department of Otolaryngology, China Medical University, Taichung, Taiwan 404iChina Medical University Hospital, Department of Otorhinolaryngology, Taichung, Taiwan 404.
authors.forename: Ming-Hsui
authors.initials: MH
authors.lastname: Tsai
authors.affiliation: China Medical University, Biomedical Engineering Research and Development Center, Taichung, Taiwan 404gNational Chiao Tung University, Department of Electrical Engineering, Hsinchu, Taiwan 300.
authors.forename: Jin-Chern
authors.initials: JC
authors.lastname: Chiou
mesh_terms: D000368:Aged; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009062:Mouth Neoplasms / Q000737:chemistry*; D061848:Optical Imaging / Q000379:methods*; D025341:Principal Component Analysis