Segmentation of MR images of the brain based on statistical and spatial properties

Joao E. Batista

doi:10.1117/12.430971

Abstract

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.

Citation Download Citation

Joao E. Batista, Joao E. Batista, "Segmentation of MR images of the brain based on statistical and spatial properties", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.430971; https://doi.org/10.1117/12.430971

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