This work evaluates brain volumetry measurements obtained from T1w images with fast (PI) and rapid (PI+CS) protocols (< 3 mins) and reconstructed with AIR Recon DL 3D, a deep learning-based reconstruction to reduce noise and ringing. Images were segmented using FDA-cleared software NeuroQuantÒ for quantitative volumetric analysis. Segmentation was successful in all cases and key brain volumes are unchanged between fast and rapid protocols, and further between conventional and DL reconstructions. This work demonstrates that highly accelerated acquisitions and advanced reconstruction methods are suitable for segmentation and volumetric studies and can improve repeatability of measurements.
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