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Segmentation of brain MR images using a proper combination of DCS based method with MRF

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Abstract

Manual segmentation of Magnetic Resonance Images (MRI) is a time-consuming process, thus automatic segmentation of brain MR images has attracted more attention in recent years. In this paper, we introduce Dynamic Classifier Selection Markov Random Field (DCSMRF) algorithm for supervised segmentation of brain MR images into three main tissues such as White Matter (WM), Gray Matter (GM) and Cerebrospinal Fluid (CSF). DCSMRF combines a novel ensemble method with the Markov Random Field (MRF) algorithm and tries to obtain the advantages of both algorithms. For the ensemble part of DCSMRF, we propose an ensemble method called Dynamic Classifier System-Weighted Local Accuracy (DCS-WLA) which is a type of Combination of Multiple Classifier (CMC) algorithm. Later, the MRF algorithm is utilized for incorporating spatial, contextual and textural information in this paper. For the MRF section, an energy function based on the output of the DCS-WLA algorithm is proposed, then maximum value for Maximum A Posterior (MAP) criterion is searched to obtain optimal segmentation. The MRF algorithm applies similar to a post processing step in which only a subset of pixels is selected for optimization step. Hence, a vast amount of search space is pruned. Consequently, the computational burden of the proposed algorithm is more tolerable than the conventional MRF-based methods. Moreover, by employing ensemble algorithms, the accuracy and reliability of final results are enhanced compared to the individual methods.

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Acknowledgements

The work has been supported by internal funding from IUST University. No external financial support has been obtained for this work.

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Authors and Affiliations

  1. School of Computer Engineering, Iran University of Science and Technology (IUST), Tehran, Iran

    Ali Ahmadvand

  2. Mathematics and Computer Science Department, Emory University, Atlanta, GA, 30322, USA

    Ali Ahmadvand

  3. Neuroscience and Neuroengineering Research Lab., Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, 16846-13114, Iran

    Mohammad Reza Daliri

  4. Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Sayyed Mohammadreza Zahiri

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  1. Ali Ahmadvand
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  2. Mohammad Reza Daliri
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  3. Sayyed Mohammadreza Zahiri
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Correspondence to Mohammad Reza Daliri.

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Ahmadvand, A., Daliri, M.R. & Zahiri, S.M. Segmentation of brain MR images using a proper combination of DCS based method with MRF. Multimed Tools Appl 77, 8001–8018 (2018). https://doi.org/10.1007/s11042-017-4696-8

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  • DOI: https://doi.org/10.1007/s11042-017-4696-8

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