Three dimensional segmentation of volume data

Most of the research in image segmentation has focused on segmenting 2D images. When 2D segmentation techniques are applied to 3D data, the potential increase in information available in the third dimension is not typically used. The 3D multiresolution texture segmentation algorithm (3D MTS) is a proposed approach for incorporating the information in the third dimension by segmenting 3D data into homogeneous volumes. The 3D MTS algorithm is based on previous work which uses texture at multiple resolutions to determine the homogeneity of regions within an image. Experiments were performed using both synthesized and real volume data. The results demonstrate that the proposed approach is robust in the presence of noise and produces accurate segmentation results. The results also show that the 2D MTS algorithm performs well on the given data, however, it is apparent that for more complex 3D textures the 3D MTS algorithm should be able to more accurately identify homogeneous regions. Further experimentation is being performed to help validate this hypothesis