Fast and Robust Unsupervised Identification of MS Lesion Change Using the Statistical Detection of Changes Algorithm.
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ABSTRACT:
SUBMITTER: Nguyen TD
PROVIDER: S-EPMC5955764 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
Publications
Fast and Robust Unsupervised Identification of MS Lesion Change Using the Statistical Detection of Changes Algorithm.
Nguyen T D TD Zhang S S Gupta A A Zhao Y Y Gauthier S A SA Wang Y Y
AJNR. American journal of neuroradiology 20180308 5
We developed a robust automated algorithm called statistical detection of changes for detecting morphologic changes of multiple sclerosis lesions between 2 T2-weighted FLAIR brain images. Results from 30 patients showed that statistical detection of changes achieved significantly higher sensitivity and specificity (0.964, 95% CI, 0.823-0.994; 0.691, 95% CI, 0.612-0.761) than with the lesion-prediction algorithm (0.614, 95% CI, 0.410-0.784; 0.281, 95% CI, 0.228-0.314), while resulting in a 49% re ...[more]
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