Hemodynamic information obtained by statistical analysis of near-IR spectroscopic images

DOIResolve DOI: http://doi.org/10.1117/12.306097
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TypeBook Chapter
Proceedings titleInfrared Spectroscopy : New Tool in Medicine
ConferenceInfrared Spectroscopy: New Tool in Medicine, January 27, 1998, San Jose, California, U. S. A.
Pages296306; # of pages: 11
Subjectvisible/near infrared multispectral imaging; principal component analysis; factor rotation; image segmentation; k-means; fuzzy c-means; hemoglobin oxygen saturation; tissue perfusion; skin flap
AbstractThe probability of transplanted skin remaining viable is often difficult to assess visually. The adverse circulatory changes following the surgical elevation of a skin flap limits the supply of oxygen to the flap tissue. Regions of tissue which experience prolonged and severe deprivation of oxygen will not survive. A dorsal rat skin flap model was used to demonstrate the potential of visible/near IR multispectral imaging to detect tissues under hypoxic stress. Images were acquired before and immediately after surgery. Image pre-processing methods were used to enhance tissue contrast and eliminate image artifacts. Principal component analysis of these images further enhanced contrast along the length of the flap while varimax rotation simplified data interpretation. Significant hemodynamic changes were detected (i) between pre- and post-operative images, and (ii) within the post-elevation flap image itself. K-means and fuzzy C-means image segmentation methods were applied to the post-operative multispectral images and proved to be reliable means of predicting regions of tissue that would go on to become visibly necrotic after a 72 h monitoring period. The result suggest that statistical analysis of visible/near IR multispectral images can be used to extract clinically relevant information pertaining to tissue hemodynamics following reconstructive surgery.
Publication date
AffiliationNational Research Council Canada; NRC Institute for Biodiagnostics
Peer reviewedYes
NRC number893
NPARC number9723500
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Record identifierf2d397e7-42c6-4a90-b90c-d802190b38f4
Record created2009-07-17
Record modified2016-10-19
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