A modified region growing based algorithm to vessel segmentation in magnetic resonance angiography

Abstract

The progress of medical imaging instrumentation has stirred the development of new computer-aided methods of image processing and analysis for better understanding and interpretation of medical images for differential diagnosis, intervention, and treatment monitoring. Image processing and analysis methods have been used to help physicians to make important medical decisions through physician-computer interaction. A modified region growing algorithm is proposed to extract cerebral vessels using a magnetic resonance angiography (MRA) database. To improve the performance of the image segmentation method, as a pre-processing step, image enhancement methods are applied by the gamma correction technique and spatial operations. This step improves the detection of gray-level discontinuities in MRA images. The traditional region growing method is modified by extending the neighborhood as 24 pixels and by defining a filling protocol to label vascular structure. The performance of the proposed algorithm is compared with that of the traditional region growing method and four other segmentation methods. Our proposed method outperformed the other methods. The minimum and maximum errors of the modified region growing method is calculated as zero and 0.82, respectively while the traditional region growing method has 1.85 and 21.91.