Vector Seeded Region Growing for parenchyma classification

Magnetic Resonance Imaging (MRI), being noninvasive and having no radiation hazards, provides abundant tissue information and has become an efficient instrument for clinical diagnoses and research in recent years. When tissues are classified by means of MRI, the images are multi-spectral. Therefore, if only a single image with a certain spectrum is processed, the goal of tissue classification will not be achieved because the single image can´t provide adequate information. Consequently, it is necessary to integrate the information of all the spectral images to classify tissues. Multi-spectral image processing techniques are hence employed to collect spectral information for classification and of clinically critical values. Based on brain MRI, this study applied Unsupervised Vector Seeded Region Growing (UVSRG) to classification, and the result indicating the possible usefulness of this method.