3 July 2001 Segmentation of MR images of the brain based on statistical and spatial properties
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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.
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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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