| 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 | 237 | 2017 |
| Depression assessment by fusing high and low level features from audio, video, and text A Pampouchidou, O Simantiraki, A Fazlollahi, M Pediaditis, D Manousos, ... Proceedings of the 6th International Workshop on Audio/Visual Emotion …, 2016 | 117 | 2016 |
| Fifteen years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study: progress and observations from 2,359 older adults spanning the spectrum from cognitive normality … C Fowler, SR Rainey-Smith, S Bird, J Bomke, P Bourgeat, BM Brown, ... Journal of Alzheimer's disease reports 5 (1), 443-468, 2021 | 65 | 2021 |
| MRI‐alone radiation therapy planning for prostate cancer: automatic fiducial marker detection S Ghose, J Mitra, D Rivest‐Hénault, A Fazlollahi, P Stanwell, P Pichler, ... Medical physics 43 (5), 2218-2228, 2016 | 48 | 2016 |
| Computer-aided detection of cerebral microbleeds in susceptibility-weighted imaging A Fazlollahi, F Meriaudeau, L Giancardo, VL Villemagne, CC Rowe, ... Computerized Medical Imaging And Graphics 46, 269-276, 2015 | 47 | 2015 |
| Increased cerebral blood flow with increased amyloid burden in the preclinical phase of alzheimer's disease A Fazlollahi, F Calamante, X Liang, P Bourgeat, P Raniga, V Dore, J Fripp, ... Journal of Magnetic Resonance Imaging 51 (2), 505-513, 2020 | 44 | 2020 |
| Cerebrospinal fluid ferritin levels predict brain hypometabolism in people with underlying β-amyloid pathology I Diouf, A Fazlollahi, AI Bush, S Ayton, ... Neurobiology of disease 124, 335-339, 2019 | 40 | 2019 |
| Efficient machine learning framework for computer-aided detection of cerebral microbleeds using the radon transform A Fazlollahi, F Meriaudeau, VL Villemagne, CC Rowe, P Yates, ... 2014 IEEE 11th international symposium on biomedical imaging (ISBI), 113-116, 2014 | 39 | 2014 |
| SHARQnet–Sophisticated harmonic artifact reduction in quantitative susceptibility mapping using a deep convolutional neural network S Bollmann, MH Kristensen, MS Larsen, MV Olsen, MJ Pedersen, ... Zeitschrift für Medizinische Physik 29 (2), 139-149, 2019 | 36 | 2019 |
| Reproducibility of multiphase pseudo-continuous arterial spin labeling and the effect of post-processing analysis methods A Fazlollahi, P Bourgeat, X Liang, F Meriaudeau, A Connelly, O Salvado, ... NeuroImage 117, 191-201, 2015 | 31 | 2015 |
| Australian Imaging Biomarkers Lifestyle (AIBL) Research Group, Salvado O, Bush AI (2017) Cerebral quantitative susceptibility mapping predicts amyloid-β-related cognitive decline S Ayton, A Fazlollahi, P Bourgeat, P Raniga, A Ng, Y Lim, I Diouf, ... Brain 140, 2112-2119, 0 | 30* | |
| Non-wearable UWB sensor to detect falls in smart home environment G Mokhtari, Q Zhang, A Fazlollahi 2017 IEEE International Conference on Pervasive Computing and Communications …, 2017 | 26 | 2017 |
| A prospective cohort study of prodromal Alzheimer’s disease: prospective imaging study of ageing: genes, brain and behaviour (PISA) MK Lupton, GA Robinson, RJ Adam, S Rose, GJ Byrne, O Salvado, ... NeuroImage: Clinical 29, 102527, 2021 | 25 | 2021 |
| Hippocampal glutathione depletion with enhanced iron level in patients with mild cognitive impairment and Alzheimer’s disease compared with healthy elderly participants PK Mandal, A Goel, AI Bush, K Punjabi, S Joon, R Mishra, M Tripathi, ... Brain communications 4 (5), fcac215, 2022 | 21 | 2022 |
| Reduced cortical cholinergic innervation measured using [18F]-FEOBV PET imaging correlates with cognitive decline in mild cognitive impairment Y Xia, E Eeles, J Fripp, D Pinsker, P Thomas, M Latter, V Doré, ... NeuroImage: Clinical 34, 102992, 2022 | 19 | 2022 |
| Robust automatic landmark detection for underwater SLAM using side-scan sonar imaging J Aulinas, A Fazlollahi, J Salvi, X Lladó, Y Petillot, J Sawas, R Garcıa Proceedings of the 11th International Conference on Mobile Robots and …, 2011 | 17 | 2011 |
| Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks Y Gao, Z Xiong, A Fazlollahi, PJ Nestor, V Vegh, F Nasrallah, C Winter, ... NeuroImage 259, 119410, 2022 | 16 | 2022 |
| Alzheimer’s disease Neuroimaging I. Cerebrospinal fluid ferritin levels predict brain hypometabolism in people with underlying beta-amyloid pathology I Diouf, A Fazlollahi, AI Bush, S Ayton Neurobiol Dis 124, 335-9, 2019 | 13 | 2019 |
| Automatic detection of small spherical lesions using multiscale approach in 3D medical images A Fazlollahi, F Meriaudeau, VL Villemagne, CC Rowe, PM Desmond, ... 2013 IEEE International Conference on Image Processing, 1158-1162, 2013 | 13 | 2013 |
| Patient with ALS with a novel TBK1 mutation, widespread brain involvement, behaviour changes and metabolic dysfunction PA McCombe, ST Ngo, CC Guo, A Fazlollahi, S Bollmann, L Wang, X Hu, ... Journal of Neurology, Neurosurgery & Psychiatry 90 (8), 952-954, 2019 | 12 | 2019 |
Olivier SalvadoCSIRO - Lead AI for MissionsVerified email at csiro.au
