Thomas, C. et al. Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited.
RESULTS Intraclass correlation coefficients of.95,.91, and.86 were observed for WML and CSF segmentation accuracy and brain parenchymal fraction (BPF).
Various localization tests were administered to ensure accuracy for brain and pelvic treatments.
To investigate the influence of naming accuracy on brain activations, we therefore (1) considered the number of errors as covariates, and (2) compared carefully matched sets of FAL and COR for subjects with higher error rates.
The success of this BCI system depends on the classification accuracy of brain signals.
The quantitative accuracy of brain PET/MR has been reported to be reduced compared to PET/CT due to difficulties related to bone in MR-based attenuation correction (MRAC), especially in regions near the skull.
However, the fact remains that, even if in an indirect manner, these new tools are increasingly able to determine with a high degree of accuracy certain brain data that belong to the private sphere and deserve to be protected from public scrutiny.
To this end, we propose a novel combination of feature extraction, selection and classification strategies which may maximize prediction accuracy for brain state classification.
Example 1: Meta-Analysis of diagnostic accuracy of Brain Natriuretic Peptides (BNP) for heart failure.
The accuracy of brain tumour grading by each technique, as well as the combination of ADC values and contrast-free pCASL sequences, was investigated in a cohort of patients with astrocytic tumours.
We therefore analyzed both behavior (as reaction times [RTs] and accuracy) and brain activity (power and ISPC) using repeated measures analysis of variance (ANOVA) with the within-subjects factors of interest Current Trial Congruency (congruent vs. incongruent) and Conflict Probability (high vs. low).
