title: Resonant Mie scattering (RMieS) correction applied to FTIR images of biological tissue samples.
abstract: Recently a resonant Mie scattering (RMieS) correction approach has been developed and demonstrated to be effective for removing the baseline distortions that compromise the raw data in individual spectra. In this paper RMieS correction is extended to FTIR images of a tissue section from biopsy of the human cervical transformation zone and a coronal tissue section of a Wistar rat brain and compared to the uncorrected images. It is shown that applying RMieS correction to FTIR images a) removes baseline distortions from the image spectra and thus reveals previously hidden information on spatial variation of chemical contents within the tissue and b) can lead to improved automatic tissue feature classification through multivariate cluster analysis.
authors.affiliation: Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton, Victoria, 3800, Australia.
authors.forename: Keith R
authors.initials: KR
authors.lastname: Bambery
authors.forename: Bayden R
authors.initials: BR
authors.lastname: Wood
authors.forename: Don
authors.initials: D
authors.lastname: McNaughton
mesh_terms: D000465:Algorithms; D000818:Animals; D016477:Artifacts; D001921:Brain / Q000378:metabolism / Q000473:pathology*; D002584:Cervix Uteri / Q000378:metabolism / Q000473:pathology*; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D003952:Diagnostic Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D051381:Rats; D012015:Reference Standards; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D014018:Tissue Distribution