title: Automatic method for the dermatological diagnosis of selected hand skin features in hyperspectral imaging.
abstract: BACKGROUND
  Hyperspectral imaging has been used in dermatology for many years. The enrichment of hyperspectral imaging with image analysis broadens considerably the possibility of reproducible, quantitative evaluation of, for example, melanin and haemoglobin at any location in the patient's skin. The dedicated image analysis method proposed by the authors enables to automatically perform this type of measurement.
  
  
  METHODS
  As part of the study, an algorithm for the analysis of hyperspectral images of healthy human skin acquired with the use of the Specim camera was proposed. Images were collected from the dorsal side of the hand. The frequency λ of the data obtained ranged from 397 to 1030 nm. A total of 4'000 2D images were obtained for 5 hyperspectral images. The method proposed in the paper uses dedicated image analysis based on human anthropometric data, mathematical morphology, median filtration, normalization and others. The algorithm was implemented in Matlab and C programs and is used in practice.
  
  
  RESULTS
  The algorithm of image analysis and processing proposed by the authors enables segmentation of any region of the hand (fingers, wrist) in a reproducible manner. In addition, the method allows to quantify the frequency content in different regions of interest which are determined automatically. Owing to this, it is possible to perform analyses for melanin in the frequency range λE∈(450,600) nm and for haemoglobin in the range λH∈(397,500) nm extending into the ultraviolet for the type of camera used. In these ranges, there are 189 images for melanin and 126 images for haemoglobin. For six areas of the left and right sides of the little finger (digitus minimus manus), the mean values of melanin and haemoglobin content were 17% and 15% respectively compared to the pattern.
  
  
  CONCLUSIONS
  The obtained results confirmed the usefulness of the proposed new method of image analysis and processing in dermatology of the hand as it enables reproducible, quantitative assessment of any fragment of this body part. Each image in a sequence was analysed in this way in no more than 100 ms using Intel Core i5 CPU M460 @2.5 GHz 4 GB RAM.
authors.affiliation: Department of Biomedical Computer Systems, University of Silesia, Faculty of Computer Science and Materials Science, Institute of Computer Science, ul, Będzińska 39, Sosnowiec 41-200, Poland. robert.koprowski@us.edu.pl.
authors.forename: Robert
authors.initials: R
authors.lastname: Koprowski
authors.forename: Sławomir
authors.initials: S
authors.lastname: Wilczyński
authors.forename: Zygmunt
authors.initials: Z
authors.lastname: Wróbel
authors.forename: Sławomir
authors.initials: S
authors.lastname: Kasperczyk
authors.forename: Barbara
authors.initials: B
authors.lastname: Błońska-Fajfrowska
mesh_terms: D000465:Algorithms; D001331:Automation; D006225:Hand; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008543:Melanins / Q000378:metabolism; D057054:Molecular Imaging / Q000379:methods*; D012867:Skin / Q000378:metabolism*
chemical_list: D006454:Hemoglobins; D008543:Melanins
references.citation: J Mod Opt. 2011;58(19-20):1781-1787
references.pmid: 22865954
references.citation: J Biophotonics. 2011 Oct;4(10):759-67
references.pmid: 21595043
references.citation: Biomed Eng Online. 2013 Nov 14;12:117
references.pmid: 24224964
references.citation: Biomed Eng Online. 2012 Jun 22;11:35
references.pmid: 22727245
references.citation: J Biomed Opt. 2011 Feb;16(2):026009
references.pmid: 21361693
references.citation: Appl Opt. 2007 Dec 1;46(34):8328-34
references.pmid: 18059676
references.citation: J Biomed Opt. 2011 Aug;16(8):086014
references.pmid: 21895326
references.citation: J Biomed Opt. 2012 Jul;17(7):076005
references.pmid: 22894488
references.citation: J Endourol. 2013 Apr;27(4):470-4
references.pmid: 23067098
references.citation: Biomed Opt Express. 2012 Jun 1;3(6):1300-11
references.pmid: 22741077
references.citation: IEEE Trans Image Process. 2013 Mar;22(3):1134-47
references.pmid: 23193455
references.citation: J Pharm Biomed Anal. 2012 Nov;70:691-9
references.pmid: 22840977
references.citation: Analyst. 2012 Dec 21;137(24):5723-9
references.pmid: 23001149
references.citation: J Pharm Biomed Anal. 2012 Nov;70:680-90
references.pmid: 22818029
references.citation: J Biomed Opt. 2006 Sep-Oct;11(5):054012
references.pmid: 17092161
references.citation: Forensic Sci Int. 2012 Nov 30;223(1-3):72-7
references.pmid: 22938693
references.citation: Cancer Biol Ther. 2006 Aug;5(8):1033-8
references.pmid: 16931902
references.citation: Am J Physiol Heart Circ Physiol. 2003 Sep;285(3):H1183-9
references.pmid: 12791593
references.citation: Forensic Sci Int. 2012 Nov 30;223(1-3):28-39
references.pmid: 23088824
references.citation: Cancer Sci. 2011 Apr;102(4):852-7
references.pmid: 21205093
references.citation: Neurochem Int. 2012 Dec;61(8):1375-84
references.pmid: 23059447
references.citation: Anal Chem. 2011 Oct 1;83(19):7424-30
references.pmid: 21842837
references.citation: J Endourol. 2013 Mar;27(3):265-9
references.pmid: 22973969