Keywords: AI/ML Image Reconstruction, Validation
Motivation: SmartSpeed AI, deep learning-based MR image reconstruction method can be used for scan acceleration, but its clinical applicability for studying brain volumetry and/or cortical myelin has not been investigated.
Goal(s): This study was aimed to quantitatively evaluate the reliability for estimates of cortical thickness and myelin estimated from SmartSpeed AI reconstruction.
Approach: Segmentation performance was evaluated using Dice coefficient and Hausdorff distance and the reliability of estimation for cortical thickness and myelin was assessed using intraclass correlation coefficient.
Results: Comparable segmentation accuracy and reliable estimates of cortical thickness and myelin were obtained from relatively high acceleration factor with SmartSpeed AI reconstruction.
Impact: SmartSpeed AI reconstruction enabled accurate cortical segmentation, and the reliable estimation of cortical thickness and intracortical myelin, suggesting the validity of its clinical applicability with reduced scan time.
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