| Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging CC Rowe, KA Ellis, M Rimajova, P Bourgeat, KE Pike, G Jones, J Fripp, ... Neurobiology of aging 31 (8), 1275-1283, 2010 | 1143 | 2010 |
| Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan R Pomponio, G Erus, M Habes, J Doshi, D Srinivasan, E Mamourian, ... NeuroImage 208, 116450, 2020 | 424 | 2020 |
| An atlas-based electron density mapping method for magnetic resonance imaging (MRI)-alone treatment planning and adaptive MRI-based prostate radiation therapy JA Dowling, J Lambert, J Parker, O Salvado, J Fripp, A Capp, C Wratten, ... International Journal of Radiation Oncology* Biology* Physics 83 (1), e5-e11, 2012 | 379 | 2012 |
| A novel mesh processing based technique for 3D plant analysis A Paproki, X Sirault, S Berry, R Furbank, J Fripp BMC plant biology 12, 1-13, 2012 | 303 | 2012 |
| Symmetric diffeomorphic registration of fibre orientation distributions D Raffelt, JD Tournier, J Fripp, S Crozier, A Connelly, O Salvado Neuroimage 56 (3), 1171-1180, 2011 | 302 | 2011 |
| MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide VM Bashyam, G Erus, J Doshi, M Habes, IM Nasrallah, M Truelove-Hill, ... Brain 143 (7), 2312-2324, 2020 | 286 | 2020 |
| Ea-GANs: edge-aware generative adversarial networks for cross-modality MR image synthesis B Yu, L Zhou, L Wang, Y Shi, J Fripp, P Bourgeat IEEE transactions on medical imaging 38 (7), 1750-1762, 2019 | 282 | 2019 |
| Cerebral quantitative susceptibility mapping predicts amyloid-β-related cognitive decline S Ayton, A Fazlollahi, P Bourgeat, P Raniga, A Ng, YY Lim, I Diouf, ... Brain 140 (8), 2112-2119, 2017 | 264 | 2017 |
| β-Amyloid burden in the temporal neocortex is related to hippocampal atrophy in elderly subjects without dementia P Bourgeat, G Chetelat, VL Villemagne, J Fripp, P Raniga, K Pike, ... Neurology 74 (2), 121-127, 2010 | 257 | 2010 |
| Automatic segmentation and quantitative analysis of the articular cartilages from magnetic resonance images of the knee J Fripp, S Crozier, SK Warfield, S Ourselin IEEE transactions on medical imaging 29 (1), 55-64, 2009 | 232 | 2009 |
| Cross-sectional and longitudinal analysis of the relationship between Aβ deposition, cortical thickness, and memory in cognitively unimpaired individuals and in Alzheimer disease V Doré, VL Villemagne, P Bourgeat, J Fripp, O Acosta, G Chetélat, L Zhou, ... JAMA neurology 70 (7), 903-911, 2013 | 216 | 2013 |
| Automatic substitute computed tomography generation and contouring for magnetic resonance imaging (MRI)-alone external beam radiation therapy from standard MRI sequences JA Dowling, J Sun, P Pichler, D Rivest-Hénault, S Ghose, H Richardson, ... International Journal of Radiation Oncology* Biology* Physics 93 (5), 1144-1153, 2015 | 182 | 2015 |
| A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective AM Pagnozzi, E Conti, S Calderoni, J Fripp, SE Rose International Journal of Developmental Neuroscience 71, 68-82, 2018 | 168 | 2018 |
| Lesion segmentation from multimodal MRI using random forest following ischemic stroke J Mitra, P Bourgeat, J Fripp, S Ghose, S Rose, O Salvado, A Connelly, ... NeuroImage 98, 324-335, 2014 | 165 | 2014 |
| Automatic segmentation of the bone and extraction of the bone–cartilage interface from magnetic resonance images of the knee J Fripp, S Crozier, SK Warfield, S Ourselin Physics in Medicine & Biology 52 (6), 1617, 2007 | 160 | 2007 |
| 3D cGAN based cross-modality MR image synthesis for brain tumor segmentation B Yu, L Zhou, L Wang, J Fripp, P Bourgeat 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018 …, 2018 | 145 | 2018 |
| Comparison of MR-less PiB SUVR quantification methods P Bourgeat, VL Villemagne, V Dore, B Brown, SL Macaulay, R Martins, ... Neurobiology of aging 36, S159-S166, 2015 | 138 | 2015 |
| Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models K Shen, J Fripp, F Mériaudeau, G Chételat, O Salvado, P Bourgeat, ... Neuroimage 59 (3), 2155-2166, 2012 | 137 | 2012 |
| The Brain Chart of Aging: machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 … M Habes, R Pomponio, H Shou, J Doshi, E Mamourian, G Erus, ... Alzheimer's & Dementia 17 (1), 89-102, 2021 | 135 | 2021 |
| Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models A Neubert, J Fripp, C Engstrom, R Schwarz, L Lauer, O Salvado, ... Physics in Medicine & Biology 57 (24), 8357, 2012 | 134 | 2012 |
Pierrick BourgeatCSIRO eHealth Research Centre - Biomedical Informatics Group – Image analysis Team , AustraliaVerified email at csiro.au
