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Computational analysis of PET by AIBL (CapAIBL): a cloud-based processing pipeline for the quantification of PET images.

, , , , , and . Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 94132V. SPIE, (2015)

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β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3., , , , , , , , , and 5 other author(s). NeuroImage, (2022)Implementing the centiloid transformation for 11C-PiB and β-amyloid 18F-PET tracers using CapAIBL., , , , , , , and . NeuroImage, (2018)PET-only 18F-AV1451 tau quantification., , , , , , , and . ISBI, page 1173-1176. IEEE, (2017)A Framework to Objectively Identify Reference Regions for Normalizing Quantitative Imaging., , , , , , , , , and 3 other author(s). MICCAI (1), volume 11070 of Lecture Notes in Computer Science, page 65-72. Springer, (2018)PET image harmonization using smoothing-CycleGAN., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)Computational analysis of PET by AIBL (CapAIBL): a cloud-based processing pipeline for the quantification of PET images., , , , , and . Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 94132V. SPIE, (2015)A normalisation framework for quantitative brain imaging; application to quantitative susceptibility mapping., , , , , , , , , and 2 other author(s). ISBI, page 97-100. IEEE, (2017)Non-negative matrix factorisation improves Centiloid robustness in longitudinal studies., , , , , , , and . NeuroImage, (2021)CapAIBL: Automated Reporting of Cortical PET Quantification Without Need of MRI on Brain Surface Using a Patch-Based Method., , , , , , , , and . Patch-MI@MICCAI, volume 9993 of Lecture Notes in Computer Science, page 109-116. (2016)