Fast and Robust Unsupervised Identification of MS Lesion Change Using the Statistical Detection of Changes Algorithm [ADULT BRAIN]
SUMMARY:
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% reduction in human review time (P = .007).
Source: American Journal of Neuroradiology - Category: Radiology Authors: Nguyen, T. D., Zhang, S., Gupta, A., Zhao, Y., Gauthier, S. A., Wang, Y. Tags: ADULT BRAIN Source Type: research