Quantification of morphological change of cerebral blood vessels using three-dimensional fractal analysis and magnetic resonance angiography

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Magnetic resonance angiography (MRA) has currently played a useful role as a noninvasive method of surveying vascular anatomy. In this study, we developed an automated seeded region growing algorithm for extraction of blood vessles from MRA data. In the conventional region growing algorithm, the user must manually place a seed point within a large blood vessel and also input the segmentation threshold. Furthermore, these processes must be repeated with a different set of seeds and threshold until the satisfactory results are obtained. Thus, this method is time- consuming and the results obtained by this method are highly subjective to the user. With our algorithm, binary images were firstly generated by thresholding the original MRA data to roughly obtained images of blood vessels, and then the skeletons were used for region growing. Our method extracted blood vessels automatically and stably, and the segmentation leakage could be largely suppressed. In conclusion, our automated seeded region growing algorithm appears to be useful for extracting and displaying blood vessels.