4.1 Article Data Paper

Data on MRI brain lesion segmentation using K-means and Gaussian Mixture Model-Expectation Maximization

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DATA IN BRIEF
Volume 27, Issue -, Pages -

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ELSEVIER
DOI: 10.1016/j.dib.2019.104628

Keywords

Ischemic stroke; Lesion; Magnetic resonance image (MRI); Segmentation

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The data in this article provide details about MRI lesion segmentation using K-means and Gaussian Mixture Model-Expectation Maximization (GMM-EM) algorithms. Both K-means and GMM-EM algorithms can segment lesion area from the rest of brain MRI automatically. The performance metrics (accuracy, sensitivity, specificity, false positive rate, misclassification rate) were estimated for the algorithms and there was no significant difference between K-means and GMM-EM. In addition, lesion size does not affect the accuracy and sensitivity for either method. (c) 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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