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Amir Fazlollahi
Amir Fazlollahi
Research Fellow, Queensland Brain Institute, University of Queensland
Verified email at uq.edu.au
Title
Cited by
Cited by
Year
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
2472017
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
1212016
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
792021
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
492016
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
462015
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
442020
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
412019
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
392014
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
372019
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
342015
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
32*
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
272021
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
262022
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
262022
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
262017
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
192022
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
172011
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
132019
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
122019
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
122013
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