Open Access
1 May 2010 Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal
Dewen Hu, Yucheng Wang, Yadong Liu, Ming Li, Fayi Liu
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Abstract
An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.
©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Dewen Hu, Yucheng Wang, Yadong Liu, Ming Li, and Fayi Liu "Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal," Journal of Biomedical Optics 15(3), 036025 (1 May 2010). https://doi.org/10.1117/1.3456371
Published: 1 May 2010
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Veins

Arteries

Image segmentation

Optical imaging

Cerebral cortex

Capillaries

Hemodynamics

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