Blood vessel segmentation in magnetic resonance angiography imagery

S. P. Kozaitis; R. Chandramohan

doi:10.1117/12.882897

3 June 2011 Blood vessel segmentation in magnetic resonance angiography imagery

S. P. Kozaitis, R. Chandramohan

Proceedings Volume 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX; 805810 (2011) https://doi.org/10.1117/12.882897
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Small blood vessels may be difficult to detect in magnetic resonance angiography due to the lack of blood flow caused by disease or injury. Our method, which uses a block-matching denoising approach to segment blood vessels, works well in the presence of noise. We examined extended regions of an image to determine whether they contained blood vessels by fitting a Gaussian mixture model to a region's histogram. Then, dissimilar regions were denoised separately. This approach was beneficial in low-contrast settings. It can be used to detect higher-order blood vessels that may be difficult to detect under normal conditions.

Citation Download Citation

S. P. Kozaitis and R. Chandramohan "Blood vessel segmentation in magnetic resonance angiography imagery", Proc. SPIE 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX, 805810 (3 June 2011); https://doi.org/10.1117/12.882897

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