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2024

Journal Article

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET

Moradi, Hamed, Vashistha, Rajat, O’Brien, Kieran, Hammond, Amanda, Vegh, Viktor and Reutens, David (2024). A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET. EJNMMI Research, 14 (1) 1, 1-14. doi: 10.1186/s13550-023-01061-7

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET

2024

Journal Article

Intranasal delivery of imaging agents to the brain

Almahmoud, Abdallah, Parekh, Harendra S., Paterson, Brett M., Tupally, Karnaker Reddy and Vegh, Viktor (2024). Intranasal delivery of imaging agents to the brain. Theranostics, 14 (13), 5022-5101. doi: 10.7150/thno.98473

Intranasal delivery of imaging agents to the brain

2024

Conference Publication

An unsupervised deep learning-based method for in vivo high resolution Kidney MRI motion correction

Moinian, Shahrzad, Kurniawan, Nyoman, Chandra, Shekhar, Vegh, Viktor and Reutens, David (2024). An unsupervised deep learning-based method for in vivo high resolution Kidney MRI motion correction. 2023 ISMRM & ISMRT Annual Meeting & Exhibition, Toronto, ON, Canada, 3-8 June 2023. Berkeley, CA, United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2023/4915

An unsupervised deep learning-based method for in vivo high resolution Kidney MRI motion correction

2024

Journal Article

ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages

Vashistha, Rajat, Moradi, Hamed, Hammond, Amanda, O’Brien, Kieran, Rominger, Axel, Sari, Hasan, Shi, Kuangyu, Vegh, Viktor and Reutens, David (2024). ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages. EJNMMI Research, 14 (1) 10, 1-13. doi: 10.1186/s13550-024-01072-y

ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages

2024

Conference Publication

Interpretable 3D multi-modal residual convolutional neural network for mild traumatic brain injury diagnosis

Ellethy, Hanem, Vegh, Viktor and Chandra, Shekhar S. (2024). Interpretable 3D multi-modal residual convolutional neural network for mild traumatic brain injury diagnosis. 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, Brisbane, QLD, Australia, 28 November – 1 December 2023. Singapore, Singapore: Springer Nature Singapore. doi: 10.1007/978-981-99-8388-9_39

Interpretable 3D multi-modal residual convolutional neural network for mild traumatic brain injury diagnosis

2023

Journal Article

An unsupervised deep learning-based image translation method for retrospective motion correction of high resolution kidney MRI

Moinian, Shahrzad, Kurniawan, Nyoman D., Chandra, Shekhar S., Vegh, Viktor and Reutens, David C. (2023). An unsupervised deep learning-based image translation method for retrospective motion correction of high resolution kidney MRI. Intelligence-Based Medicine, 8 100108, 1-15. doi: 10.1016/j.ibmed.2023.100108

An unsupervised deep learning-based image translation method for retrospective motion correction of high resolution kidney MRI

2023

Journal Article

Hippocampal demyelination is associated with increased magnetic susceptibility in a mouse model of concussion

To, Xuan Vinh, Vegh, Viktor, Owusu-Amoah, Naana, Cumming, Paul and Nasrallah, Fatima A. (2023). Hippocampal demyelination is associated with increased magnetic susceptibility in a mouse model of concussion. Experimental Neurology, 365 114406, 1-10. doi: 10.1016/j.expneurol.2023.114406

Hippocampal demyelination is associated with increased magnetic susceptibility in a mouse model of concussion

2023

Conference Publication

SPECT image synthesis from MRI or PET using machine learning

Fard, Azin Shokraei, Reutens, David, Ramsay, Stuart, Goodman, Steven and Vegh, Viktor (2023). SPECT image synthesis from MRI or PET using machine learning. 55th Annual Conference of the Society-of-Nuclear-Medicine (SNMICON), Jodhpur India, Nov 16-19, 2023. RESTON: SOC NUCLEAR MEDICINE INC.

SPECT image synthesis from MRI or PET using machine learning

2023

Conference Publication

Investigating the dot-compartment using diffusion MRI line scanning

Vegh, Viktor, Barrick, Thomas, Yang, Qianqian, Yu, Qiang and Cloos, Martijn (2023). Investigating the dot-compartment using diffusion MRI line scanning. Joint Annual Meeting ISMRM-ESMRMB ISMRT 31st Annual Meeting, London, United Kingdom, 7 - 12 May 2022. Berkeley, CA, United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2022/4749

Investigating the dot-compartment using diffusion MRI line scanning

2023

Conference Publication

QSM from the raw phase using an end-to-end neural network

Gao, Yang, Xiong, Zhuang, Fazlollahi, Amir, Nestor, Peter, Vegh, Viktor, Pike, G. Bruce, Crozier, Stuart, Liu, Feng and Sun, Hongfu (2023). QSM from the raw phase using an end-to-end neural network. ISMRM Annual Meeting, London, United Kingdom, 7-12 May 2022. Berkeley, CA, United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2022/4740

QSM from the raw phase using an end-to-end neural network

2023

Conference Publication

Mathematically constrained intravoxel incoherent motion (IVIM)

Wang, Jiaqiu, Barrick, Thomas, Hall, Matt, Karaman, Muge, Magin, Richard, Reiter, David, Yang, Qianqian, Yu, Qiang, Nasrallah, Fatima, Koh, Weeyao and Vegh, Viktor (2023). Mathematically constrained intravoxel incoherent motion (IVIM). Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, London, United Kingdom, 7-12 May 2022. Concord, CA United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2022/3043

Mathematically constrained intravoxel incoherent motion (IVIM)

2023

Conference Publication

Analyzing Task-based fMRI Time Series using Machine Learning

Kuan, Elaine, Vegh, Viktor, O'Brien, Kieran, Hammond, Amanda, Yaksic, Javier Urriola and Reutens, David (2023). Analyzing Task-based fMRI Time Series using Machine Learning. Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, London, United Kingdom, 7-12 May 2022. Concord, CA United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2022/1909

Analyzing Task-based fMRI Time Series using Machine Learning

2022

Journal Article

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks

Gao, Yang, Xiong, Zhuang, Fazlollahi, Amir, Nestor, Peter J., Vegh, Viktor, Nasrallah, Fatima, Winter, Craig, Pike, G. Bruce, Crozier, Stuart, Liu, Feng and Sun, Hongfu (2022). Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks. NeuroImage, 259 119410, 1-13. doi: 10.1016/j.neuroimage.2022.119410

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks

2022

Conference Publication

Radiomics biomarkers are associated with survival in patients with oesophageal adenocarcinoma

Aoude, L.G., Bonazzi, V.F., Brosda, S., Wong, B., Moradi, H., Lonie, J., Bradford, J., Bloxham, C., Atkinson, V.G., Law, P., Lampe, G., Smithers, M., Waddell, N., Vegh, V., Miles, K. and Barbour, A.P. (2022). Radiomics biomarkers are associated with survival in patients with oesophageal adenocarcinoma. ESMO Congress 2022, Singapore, 9 - 13 September 2022. Amsterdam, Netherlands: Elsevier. doi: 10.1016/j.annonc.2022.07.1357

Radiomics biomarkers are associated with survival in patients with oesophageal adenocarcinoma

2022

Journal Article

From CNNs to GANs for cross-modality medical image estimation

Shokraei Fard, Azin, Reutens, David C. and Vegh, Viktor (2022). From CNNs to GANs for cross-modality medical image estimation. Computers in Biology and Medicine, 146 105556, 105556. doi: 10.1016/j.compbiomed.2022.105556

From CNNs to GANs for cross-modality medical image estimation

2022

Journal Article

Editorial: Translatable Models and MRI Methods for Neurodegenerative Diseases

Gatto, Rodolfo G., Jelescu, Ileana O. and Vegh, Viktor (2022). Editorial: Translatable Models and MRI Methods for Neurodegenerative Diseases. Frontiers in Neuroscience, 16 919860. doi: 10.3389/fnins.2022.919860

Editorial: Translatable Models and MRI Methods for Neurodegenerative Diseases

2022

Journal Article

A CNN based software gradiometer for electromagnetic background noise reduction in low field MRI applications

Su, Jiasheng, Pellicer-Guridi, Ruben, Edwards, Thomas, Fuentes, Miguel, Rosen, Matthew S., Vegh, Viktor and Reutens, David (2022). A CNN based software gradiometer for electromagnetic background noise reduction in low field MRI applications. IEEE Transactions on Medical Imaging, 41 (5), 1007-1016. doi: 10.1109/TMI.2022.3147450

A CNN based software gradiometer for electromagnetic background noise reduction in low field MRI applications

2022

Conference Publication

In vivo microstructural border delineation between areas of the human cerebral cortex using magnetic resonance fingerprinting (MRF) residuals

Moinian, Shahrzad, Vegh, Viktor and Reutens, David (2022). In vivo microstructural border delineation between areas of the human cerebral cortex using magnetic resonance fingerprinting (MRF) residuals. International Symposium for Magnetic Resonance in Medicine (ISMRM), London, United Kingdom, 7-12 May 2022. Concord, CA: ISMRM. doi: 10.58530/2022/4321

In vivo microstructural border delineation between areas of the human cerebral cortex using magnetic resonance fingerprinting (MRF) residuals

2022

Journal Article

Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals

Moinian, Shahrzad, Vegh, Viktor and Reutens, David (2022). Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals. Cerebral Cortex, 33 (5), 1550-1565. doi: 10.1093/cercor/bhac155

Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals

2022

Journal Article

The application of the distributed-order time fractional Bloch model to magnetic resonance imaging

Yu, Qiang, Turner, Ian, Liu, Fawang and Vegh, Viktor (2022). The application of the distributed-order time fractional Bloch model to magnetic resonance imaging. Applied Mathematics and Computation, 427 127188, 127188. doi: 10.1016/j.amc.2022.127188

The application of the distributed-order time fractional Bloch model to magnetic resonance imaging