Corneal thermal damage quantification from birefringence image analysis using morphological filtering

Tom J. McMurray; Colin L. Smithpeter; Ashley J. Welch; Henry Grady Rylander III; John Anthony Pearce

doi:10.1117/12.182942

17 August 1994 Corneal thermal damage quantification from birefringence image analysis using morphological filtering

Tom J. McMurray, Colin L. Smithpeter, Ashley J. Welch, Henry Grady Rylander III, John Anthony Pearce

Proceedings Volume 2134, Laser-Tissue Interaction V; and Ultraviolet Radiation Hazards; (1994) https://doi.org/10.1117/12.182942
Event: OE/LASE '94, 1994, Los Angeles, CA, United States

Abstract

Decreased corneal collagen birefringence in transmission polarizing microscopy is an observable quantitative measure of degree of tissue damage. a damage assessment algorithm based on monochrome tissue images exhibiting decreased birefringence is presented, identifying image regions with designated damage values. Initially, several video frames of the microscopic tissue image are time-averaged to reduce additive noise components, and an additional multiplicative correction for optical nonuniformities is performed. Subsequently, linear scaling improves the low contrast of the birefringence image by increasing the image value set to the standard 8-bit range of integers in the interval. Finally, morphological erosion employing a 5 X 5 pixel template reduces impulsive bright tissue artifacts. Formal damage quantification consists of a 25 X 25 pixel template mean filtering of the image, followed by background subtraction and scaling. This produces the components required for the damage computation according to the volume fraction kinetic damage model. In this investigation, the corneal damage region resembles and edge. Therefore, standard edge detection algorithms applied to the eroded image are compared the damage region identified by this algorithm. This damage quantification algorithm provides significantly superior edge delineation relative to Roberts, Sobel, Frei-Chen, Laplacian of Gaussian, and Blur-Minimum and Erosion Residue morphological edge detection algorithms.

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Tom J. McMurray, Colin L. Smithpeter, Ashley J. Welch, Henry Grady Rylander III, and John Anthony Pearce "Corneal thermal damage quantification from birefringence image analysis using morphological filtering", Proc. SPIE 2134, Laser-Tissue Interaction V; and Ultraviolet Radiation Hazards, (17 August 1994); https://doi.org/10.1117/12.182942

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KEYWORDS

Birefringence

Image filtering

Detection and tracking algorithms

Image analysis

Optical filters

Tissues

Edge detection

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