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25 May 1989 Strategies for the Segmentation of Subcutaneous Vascular Patterns in Thermographic Images
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Abstract
Computer-assisted segmentation of vascular patterns in thermographic images provides the clinician with graphic outlines of thermally significant subcutaneous blood vessels. Segmentation strategies compared here consist of image smoothing protocols followed by thresholding and zero-crossing edge detectors. Median prefiltering followed by the Frei-Chen algorithm gave the most reproducible results, with an execution time of 143 seconds for 256 X 256 images. The Laplacian of Gaussian operator was not suitable due to streak artifacts in the thermographic imaging system. This computerized process may be adopted in a fast paced clinical environment to aid in the diagnosis and assessment of peripheral circulatory diseases, Raynaud's Disease3, phlebitis, varicose veins, as well as diseases of the autonomic nervous system. The same methodology may be applied to enhance the appearance of abnormal breast vascular patterns, and hence serve as an adjunct to mammography in the diagnosis of breast cancer. The automatically segmented vascular patterns, which have a hand drawn appearance, may also be used as a data reduction precursor to higher level pattern analysis and classification tasks.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric K. Y. Chan and John A. Pearce "Strategies for the Segmentation of Subcutaneous Vascular Patterns in Thermographic Images", Proc. SPIE 1092, Medical Imaging III: Image Processing, (25 May 1989); https://doi.org/10.1117/12.953283
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