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Computer-assisted delineation of cerebral infarct from diffusion-weighted MRI using Gaussian mixture model

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Diffusion-weighted imaging (DWI) is a widely used medical imaging modality for diagnosis and monitoring of cerebral stroke. The identification of exact location of stroke lesion helps in perceiving its characteristics, an essential part of diagnosis and treatment planning. This task is challenging due to the typical shape of the stroke lesion. This paper proposes an efficient method for computer-aided delineation of stroke lesions from DWI images.

Method

Proposed methodology comprises of three steps. At the initial step, image contrast has been improved by applying fuzzy intensifier leading to the better visual quality of the stroke lesion. In the following step, a two-class (stroke lesion area vs. non-stroke lesion area) segmentation technique based on Gaussian mixture model has been designed for the localization of stroke lesion. To eliminate the artifacts which would appear during segmentation process, a binary morphological post-processing through area operator has been defined for exact delineation of the lesion area.

Result

The performance of the proposed methodology has been compared with the manually delineated images (ground truth) obtained from different experts, individually. Quantitative evaluation with respect to various performance measures (such as dice coefficient, Jaccard score, and correlation coefficient) shows the efficient performance of the proposed technique.

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Acknowledgements

The authors would like to acknowledge EKO CT and MRI Scan Centre, Medical College and Hospitals Campus, Kolkata, and Apollo Multispecialty Hospital for providing image data for this study.Funding This work was funded by Board of Research in Nuclear Sciences (BRNS), Dept. of Atomic Energy, Govt. of India (Grant number: 2013/36/38 dated: 25/11/2013).

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Authors and Affiliations

  1. School of Medical Science and Technology, IIT Kharagpur, Kharagpur, WB, 721302, India

    Manas Kumar Nag, Subhranil Koley & Chandan Chakraborty

  2. Advanced Technology Development Centre, IIT Kharagpur, Kharagpur, WB, 721302, India

    Debarghya China

  3. EKO CT and MRI Scan Centre, Medical College and Hospitals Campus, Kolkata, WB, 700082, India

    Anup Kumar Sadhu

  4. Apollo Multispecialty Hospital, Chennai, TN, 600035, India

    Ravikanth Balaji & Siddharth Ghosh

Authors
  1. Manas Kumar Nag
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  2. Subhranil Koley
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  3. Debarghya China
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  4. Anup Kumar Sadhu
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  5. Ravikanth Balaji
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  7. Chandan Chakraborty
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Correspondence to Chandan Chakraborty.

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The authors declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all participants included in the study.

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Nag, M.K., Koley, S., China, D. et al. Computer-assisted delineation of cerebral infarct from diffusion-weighted MRI using Gaussian mixture model. Int J CARS 12, 539–552 (2017). https://doi.org/10.1007/s11548-017-1520-x

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  • DOI: https://doi.org/10.1007/s11548-017-1520-x

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