Segmentation of MR images of the brain based on statistical and spatial properties
Joao E. Batista · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
Segmentation solely based on statistical approaches do not take into account spatial properties of the images. However, regions are not only characterized in statistical terms. Structural and/or spatial properties are also important and should be both considered. This paper presents a method which incorporates statistical and spatial image properties under a unified scheme for segmentation of MR images of the brain. It combines a pyramidal or quad-tree smoothing operation with statistical segmentation performed at variable levels of the quad-tree, followed by a download boundary estimation. After the segmentation step (k-means clustering algorithm), all regions and their belonging pixels are computed and stored on a data structure suitable for the quad-tree smoothing and boundary estimation. This paper describes this technique in detail and shows some results obtained on both test and MR data.