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Rates of brain atrophy over time in autopsy-proven frontotemporal dementia and Alzheimer disease.

, , , , , , , , and . NeuroImage, 39 (3): 1034-1040 (2008)

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Quantitative characterization of brain β-amyloid using a joint PiB/FDG PET image histogram., , , , , , , , , and 1 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 9035 of SPIE Proceedings, page 90352A. SPIE, (2014)Quantitative characterization of brain β-amyloid in 718 normal subjects using a joint PiB/FDG PET image histogram., , , , , , , , , and 1 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 9785 of SPIE Proceedings, page 97852V. SPIE, (2016)Accelerated vs. unaccelerated serial MRI based TBM-SyN measurements for clinical trials in Alzheimer's disease., , , , , , , , , and 6 other author(s). NeuroImage, (2015)Changing the face of neuroimaging research: Comparing a new MRI de-facing technique with popular alternatives., , , , , , , , , and 2 other author(s). NeuroImage, (2021)Detection of Dementia Signals from Longitudinal Clinical Visits Using One-Class Classification., , , , , , and . ICHI, page 211-216. IEEE, (2022)Relationships between β-amyloid and tau in an elderly population: An accelerated failure time modelww., , , , , , , , , and 3 other author(s). NeuroImage, (2021)Optimizing PiB-PET SUVR change-over-time measurement by a large-scale analysis of longitudinal reliability, plausibility, separability, and correlation with MMSE., , , , , , , , , and 1 other author(s). NeuroImage, (2017)Selecting software pipelines for change in flortaucipir SUVR: Balancing repeatability and group separation., , , , , , , , , and 6 other author(s). NeuroImage, (2021)Face recognition from research brain PET: An unexpected PET problem., , , , , , , , , and 1 other author(s). NeuroImage, (2022)Developing Safety Standards for Electromagnetic Energy: The IEEE International Committee on Electromagnetic Safety (ICES)., and . EMBC, page 4081-4084. IEEE, (2006)