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Proceedings Paper

A fully automatic unsupervised segmentation framework for the brain tissues in MR images
Author(s): Qaiser Mahmood; Artur Chodorowski; Babak Ehteshami Bejnordi; Mikael Persson
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Paper Abstract

This paper presents a novel fully automatic unsupervised framework for the segmentation of brain tissues in magnetic resonance (MR) images. The framework is a combination of our proposed Bayesian-based adaptive mean shift (BAMS), a priori spatial tissue probability maps and fuzzy c-means. BAMS is applied to cluster the tissues in the joint spatialintensity feature space and then a fuzzy c-means algorithm is employed with initialization by a priori spatial tissue probability maps to assign the clusters into three tissue types; white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The proposed framework is validated on multimodal synthetic as well as on real T1-weighted MR data with varying noise characteristics and spatial intensity inhomogeneity. The performance of the proposed framework is evaluated relative to our previous method BAMS and other existing adaptive mean shift framework. Both of these are based on the mode pruning and voxel weighted k-means algorithm for classifying the clusters into WM, GM and CSF tissue. The experimental results demonstrate the robustness of the proposed framework to noise and spatial intensity inhomogeneity, and that it exhibits a higher degree of segmentation accuracy in segmenting both synthetic and real MR data compared to competing methods.

Paper Details

Date Published: 13 March 2014
PDF: 9 pages
Proc. SPIE 9038, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging, 90381M (13 March 2014); doi: 10.1117/12.2043646
Show Author Affiliations
Qaiser Mahmood, Chalmers Univ. of Technology (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Artur Chodorowski, Chalmers Univ. of Technology (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Babak Ehteshami Bejnordi, Radboud Univ. Medical Ctr. (Netherlands)
Mikael Persson, Chalmers Univ. of Technology (Sweden)
Sahlgrenska Univ. Hospital (Sweden)


Published in SPIE Proceedings Vol. 9038:
Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging
Robert C. Molthen; John B. Weaver, Editor(s)

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