Tissue viability by multispectral near infrared imaging : a fuzzy C-means clustering analysis

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DOIResolve DOI: http://doi.org/10.1109/42.746634
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TypeArticle
Journal titleIEEE Transactions on Medical Imaging
Volume17
Issue6
Pages10111018; # of pages: 8
SubjectFuzzy clustering; image analysis; multispectral imaging; tissue viability
AbstractClinically, skin color, temperature, and capillary perfusion are used to assess tissue viability following microvascular tissue transfer. However, clinical signs that arise as a consequence of poor perfusion become evident only after several hours of compromised perfusion. This study demonstrates the potential usefulness of optical/infrared multispectral imaging in the prognosis of tissue viability immediately post-surgery. Multispectral images of a skin flap model acquired within 1 h of surgical elevation are analyzed in comparison to the final 72-h clinical outcome with a high degree of correlation. Regional changes in tissue perfusion and oxygenation present immediately following surgery are differentiated using fuzzy clustering and image processing algorithms. These methodologies reduce the intersubject variability inherent in infrared imaging methods such that the changes in perfusion are reproducible and clearly distinguishable across all subjects. Clinically, an early prognostic indicator of viability such as this would allow for a more timely intervention following surgery in the event of compromised microvasculature.
Publication date
PublisherIEEE
LanguageEnglish
AffiliationNRC Institute for Biodiagnostics; National Research Council Canada
Peer reviewedYes
NRC number907
NPARC number9148525
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Record identifier1aaca945-1b2e-4997-8a81-f6f31101ec5c
Record created2009-06-25
Record modified2016-10-13
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