Image segmentation and tissue characterization in three-dimensional intravascular ultrasound images

Xiangmin Zhang; Steven C. DeJong; Charles R. McKay M.D.; Milan Sonka

doi:10.1117/12.274102

25 April 1997 Image segmentation and tissue characterization in three-dimensional intravascular ultrasound images

Xiangmin Zhang, Steven C. DeJong, Charles R. McKay M.D., Milan Sonka

Proceedings Volume 3034, Medical Imaging 1997: Image Processing; (1997) https://doi.org/10.1117/12.274102
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

Abstract

In this paper, we report an automated approach to plaque tissue characterization in three-dimensional intravascular ultrasound images. Our previously reported automated method for coronary wall and plaque segmentation in intravascular ultrasound pullback sequences represent the first step of the method. Tissue characterization into two classes of soft and hard plaque is based on texture analysis and pattern recognition. Texture description features included gray- level-based measures, co-occurrence matrices, run length measures, and fractal-based measures. Performance of the method was assessed in cadaveric coronary arteries by comparison to the observer-defined plaque composition. Overall classification correctness of 90% was achieved.

Citation Download Citation

Xiangmin Zhang, Steven C. DeJong, Charles R. McKay M.D., and Milan Sonka "Image segmentation and tissue characterization in three-dimensional intravascular ultrasound images", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); https://doi.org/10.1117/12.274102

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