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Sørensen-Dice coefficient (DSC) and partial AUC (pAUC) values for the MIMoSA models in replication of bootstrap cross-validation under exclusion of the Proton Density-weighted (PD) sequence, the T2-weighted (T2) sequence, both PD and T2, and reducing the training set sample size to 20 subjects.

Journal: Journal of neuroimaging : official journal of the American Society of Neuroimaging

Article Title: MIMoSA: An Automated Method for Inter-Modal Segmentation Analysis of Multiple Sclerosis Brain Lesions

doi: 10.1111/jon.12506

Figure Lengend Snippet: Sørensen-Dice coefficient (DSC) and partial AUC (pAUC) values for the MIMoSA models in replication of bootstrap cross-validation under exclusion of the Proton Density-weighted (PD) sequence, the T2-weighted (T2) sequence, both PD and T2, and reducing the training set sample size to 20 subjects.

Article Snippet: The first included 98 subjects imaged at Johns Hopkins Hospital in which bootstrap cross-validation was used to compare the performance of MIMoSA against OASIS and LesionTOADS, two popular automatic segmentation approaches.

Techniques: Sequencing