Data on MRI brain lesion segmentation using K-means and Gaussian Mixture Model-Expectation Maximization
Ju Qiao, Xuezhu Cai, Qian Xiao, Zhengxi Chen, Praveen P. Kulkarni, Craig F. Ferris, Sagar V. Kamarthi, Srinivas Sridhar · Data in Brief · 2019
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.