2011
DOI: 10.1016/j.jdermsci.2011.05.002
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Visualization and characterisation of defined hair follicle compartments by Fourier transform infrared (FTIR) imaging without labelling

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Cited by 15 publications
(15 citation statements)
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References 59 publications
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“…Fourier‐transform infrared spectroscopy (FTIR) has been used in scalp and hair analysis to produce examples for matching and differentiating single human scalp hairs and to visualise defined hair follicle compartments, in addition to other many applications reported in forensic science . Raman spectroscopy is a powerful laser spectroscopic technique that detects the characteristic vibrational energy levels of a molecule and provides structural and molecular information about the hair sample.…”
Section: Introductionmentioning
confidence: 99%
“…Fourier‐transform infrared spectroscopy (FTIR) has been used in scalp and hair analysis to produce examples for matching and differentiating single human scalp hairs and to visualise defined hair follicle compartments, in addition to other many applications reported in forensic science . Raman spectroscopy is a powerful laser spectroscopic technique that detects the characteristic vibrational energy levels of a molecule and provides structural and molecular information about the hair sample.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, the IR spectroscopic imaging technique has become a powerful tool in chemical analysis; IR microspectroscopic (IMS) imaging combines spectral and spatial information at the same time and may allow the distribution of vibrational modes on the surface to be visualized. IMS imaging is especially valuable when rough surfaces, such as febrile substrates (e.g., cellulose), are investigated because it also provides information about the surface's topography [17]. IMS imaging can also detect subtle chemical changes in tissues and cells without the use of a staining or a detecting agent [17]; it is a chemical imaging technique that can be applied to a broad range of samples and systems [17]- [19].…”
Section: Introductionmentioning
confidence: 99%
“…Raw data were imported into Matlab R2011a (MathWorks) and analyzed using the IRootLab algorithm for computational biology and vibrationalmicrospectroscopy within MATLAB [27,28]. Raw data were imported into Matlab R2011a (MathWorks) and analyzed using the IRootLab algorithm for computational biology and vibrationalmicrospectroscopy within MATLAB [27,28].…”
Section: Discussionmentioning
confidence: 99%
“…The spectra obtained by Raman analysis were initially concatenated to the 400 to 1800 cm À1 range and baseline corrected, normalized, and zeroed using LabSpec 6 software. Raw data were imported into Matlab R2011a (MathWorks) and analyzed using the IRootLab algorithm for computational biology and vibrationalmicrospectroscopy within MATLAB [27,28]. Principal component analysis plus linear discriminant analysis (PCA-LDA) is a cascading application that applies LDA to the resultant PCA factors; the quality of information produced depends on the number of PCs employed [7].…”
Section: Discussionmentioning
confidence: 99%