MRI BRAIN IMAGE SEGMENTATION BY MULTI-RESOLUTION EDGE DETECTION AND REGION SELECTION

     Many methods are available for MRI brain tissue segmentation. Since the boundaries of different tissues in MRI brain images are indistinct and the intensities of the white and gray matter are very close, the edge-based segmentation methods may not provide satisfactory results. Combining both spatial and intensity information in the image, an MRI brain image segmentation approach based on multiresolution edge detection, region selection, and intensity threshold method is designed using Matlab. The detection of white matter structure in the brain is emphasized first then multi-resolution brain image representation and segmentation procedure based on a multi-scale image filtering method is designed. Given the nature of the structural connectivity and intensity homogeneity of brain tissues, region-based methods such as region growing and subtraction to segment the brain tissue structure from the multi-resolution images are utilized. From the segmented structure, the region-of-interest (ROI) image in the structure region is derived, and then a modified segmentation of the ROI based on an automatic threshold method using our threshold selection criterion is presented. Examples on both T1 and T2 weighted MRI brain image segmentation is shown in Matlab simulation, showing finer brain tissue structures.

Reference Paper: MRI Brain Image Segmentation by Multi-Resolution Edge Detection and Region Selection

Author’s Name: H. Tanga,E.X. Wua, Q.Y. Mab, D. Gallagherc, G.M. Pereraa, and T. Zhuangd

Source: International Journal of Computer and Network Security

Year:2000


SIMULATION VIDEO DEMO                                                                                                                                     



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