Literature DB >> 9533572

Analysis of skin erythema using true-color images.

M Nischik1, C Forster.   

Abstract

This article presents a new method for analyzing the spreading of skin erythemas. These occur as a result of the cutaneous vascular axon reflex which can be evoked by a noxious stimulation of the skin. Series of true-color images of the observed skin patch were recorded using a video camera. The images were digitized and stored on computer disk. The delineation of the reddening was segmented for every image of the sequence by a newly developed image processing method. Each image taken after the noxious stimulation was compared with the baseline before the stimulation and each image point was classified as: "unchanged" or "changed skin color." To improve the classification the CIE L*a*b* color space was used. The boundaries of the erythema were extracted from the resulting binary images. Every image of a sequence was analyzed in the same way in order to follow the time course of the flare response. The erythema reaction could be determined in an objective way using this methods. The automatically detected flare sizes were independent of human observers and had a high spatial and temporal resolution. It was used for a crossover study to assess the power of new drugs which modify the blood flow of the skin induced by an intradermal histamine application.

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Mesh:

Year:  1997        PMID: 9533572     DOI: 10.1109/42.650868

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  3 in total

1.  Independent histogram pursuit for segmentation of skin lesions.

Authors:  David Delgado Gómez; Constantine Butakoff; Bjarne Kjaer Ersbøll; William Stoecker
Journal:  IEEE Trans Biomed Eng       Date:  2008-01       Impact factor: 4.538

2.  Electrically evoked neuropeptide release and neurogenic inflammation differ between rat and human skin.

Authors:  K Sauerstein; M Klede; M Hilliges; M Schmelz
Journal:  J Physiol       Date:  2000-12-15       Impact factor: 5.182

3.  Characterization of digital medical images utilizing support vector machines.

Authors:  Ilias G Maglogiannis; Elias P Zafiropoulos
Journal:  BMC Med Inform Decis Mak       Date:  2004-03-10       Impact factor: 2.796

  3 in total

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