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An Effective Method for Segmentation of MR Brain Images Using the Ant Colony Optimization Algorithm

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Abstract

Since segmentation of magnetic resonance images is one of the most important initial steps in brain magnetic resonance image processing, success in this part has a great influence on the quality of outcomes of subsequent steps. In the past few decades, numerous methods have been introduced for classification of such images, but typically they perform well only on a specific subset of images, do not generalize well to other image sets, and have poor computational performance. In this study, we provided a method for segmentation of magnetic resonance images of the brain that despite its simplicity has a high accuracy. We compare the performance of our proposed algorithm with similar evolutionary algorithms on a pixel-by-pixel basis. Our algorithm is tested across varying sets of magnetic resonance images and demonstrates high speed and accuracy. It should be noted that in initial steps, the algorithm is computationally intensive requiring a large number of calculations; however, in subsequent steps of the search process, the number is reduced with the segmentation focused only in the target area.

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Author notes

  1. Mohammad Hadi Bagheri

    Present address: Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 20 Kent Street, Second Floor, Brookline, MA, 02446, USA

Authors and Affiliations

  1. Taba Medical Imaging Center, 444 Felestin Street, Shiraz, Iran

    Mohammad Taherdangkoo

  2. Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 20 Kent Street, Second Floor, Brookline, MA, 02446, USA

    Katherine P. Andriole

  3. Department of Communications and Electronics, Faculty of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran

    Mehran Yazdi

  4. Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

    Mohammad Hadi Bagheri

Authors
  1. Mohammad Taherdangkoo
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  2. Mohammad Hadi Bagheri
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  3. Mehran Yazdi
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  4. Katherine P. Andriole
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Corresponding author

Correspondence to Mohammad Hadi Bagheri.

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Taherdangkoo, M., Bagheri, M.H., Yazdi, M. et al. An Effective Method for Segmentation of MR Brain Images Using the Ant Colony Optimization Algorithm. J Digit Imaging 26, 1116–1123 (2013). https://doi.org/10.1007/s10278-013-9596-5

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  • DOI: https://doi.org/10.1007/s10278-013-9596-5

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