Dr Kieran O'Brien
Dr

Kieran O'Brien

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Background

Dr Kieran O'Brien is a Siemens Healthcare Adjunct Research Fellow at the Centre for Advanced Imaging. He completed his Bachelor of Biomedical Engineering (Honours, 2005) and PhD in Bioengineering from the University of Auckland in 2009. After being awarded his PhD Kieran worked in Postdoctoral positions at the University of Auckland and the University of Geneva Centre d'Imagerie BioMédicale before joining Siemens as a Senior Scientist in 2013.

His research interests are include improving RF pulses at high field (≥3T) to overcome imaging inhomogeneity and B1 limitations for Neuro, MSK and Cardiac applications; bi-exponential diffusion imaging; and, phase imaging for quantitative susceptibility mapping and measuring motion.

Availability

Dr Kieran O'Brien is:
Available for supervision

Fields of research

Biomedical and Clinical Sciences Biomedical engineering Clinical sciences Engineering Medical devices

Research impacts

Kieran has developed expertise as a sequence and image reconstruction software programmer for Siemens MR Scanners; developing, implementing and validating new advanced image acquisition and reconstruction techniques that overcome clinical and physical problems into commercial products. He has been responsible for leading the management of sequence projects to translate basic research from the lab on to Siemens scanners as software products that can be distributed to researchers worldwide. Of particular note is his involvement in the upgrade and development of the software for the new 7T Terra clinical system.

Search Professor Kieran O'Brien’s works on UQ eSpace

87 works between 2008 and 2025
All (87) Journal Article (57) Other Outputs (4) Conference Publication (25) Book Chapter (1)

1 - 20 of 87 works

2025

Journal Article

Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level

Domínguez D, Juan F, Stewart, Ashley, Burmester, Alex, Akhlaghi, Hamed, O'Brien, Kieran, Bollmann, Steffen and Caeyenberghs, Karen (2025). Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level. Zeitschrift für Medizinische Physik, 35 (3), 357-374. doi: 10.1016/j.zemedi.2024.01.001

Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level

2025

Journal Article

Model selection for dynamic PET compartmental modelling of 18F-FDG uptake using a long axial field-of-view PET scanner with delay and motion correction

Moradi, Hamed, Vashistha, Rajat, O’Brien, Kieran, Hammond, Amanda, Rominger, Axel, Sari, Hasan, Shi, Kuangyu, Vegh, Viktor and Reutens, David (2025). Model selection for dynamic PET compartmental modelling of 18F-FDG uptake using a long axial field-of-view PET scanner with delay and motion correction. EJNMMI Research, 15 (1) 81, 81-1. doi: 10.1186/s13550-025-01277-9

Model selection for dynamic PET compartmental modelling of 18F-FDG uptake using a long axial field-of-view PET scanner with delay and motion correction

2025

Journal Article

Non-invasive arterial input function estimation using an MRA atlas and machine learning

Vashistha, Rajat, Moradi, Hamed, Hammond, Amanda, O’Brien, Kieran, Rominger, Axel, Sari, Hasan, Shi, Kuangyu, Vegh, Viktor and Reutens, David (2025). Non-invasive arterial input function estimation using an MRA atlas and machine learning. EJNMMI Research, 15 (1) 58, 58-1. doi: 10.1186/s13550-025-01253-3

Non-invasive arterial input function estimation using an MRA atlas and machine learning

2025

Conference Publication

Economical and Diagnostic Quality Aspects Relevant for a Radiology Department Considering Implementation of Deep Learning – Augmented MRI

Bammer, Roland, Warner, Justin, Richer, Jonathan, Blackmore, Callum, Staeb, Daniel, Jin, Jin, Blagin, Roman, Anderson, Douglas, Saddik, Daniel, Stemmer, Alto, Nickel, Dominik, O'Brien, Kieran and Amukotuwa, Shalini (2025). Economical and Diagnostic Quality Aspects Relevant for a Radiology Department Considering Implementation of Deep Learning – Augmented MRI. Concord, CA: ISMRM. doi: 10.58530/2025/4891

Economical and Diagnostic Quality Aspects Relevant for a Radiology Department Considering Implementation of Deep Learning – Augmented MRI

2024

Journal Article

Language task-based fMRI analysis using machine learning and deep learning

Kuan, Elaine, Vegh, Viktor, Phamnguyen, John, O’Brien, Kieran, Hammond, Amanda and Reutens, David (2024). Language task-based fMRI analysis using machine learning and deep learning. Frontiers in Radiology, 4 1495181, 1-15. doi: 10.3389/fradi.2024.1495181

Language task-based fMRI analysis using machine learning and deep learning

2024

Journal Article

Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T

Tourell, Monique, Jin, Jin, Bachrata, Beata, Stewart, Ashley, Ropele, Stefan, Enzinger, Christian, Bollmann, Saskia, Bollmann, Steffen, Robinson, Simon Daniel, O'Brien, Kieran and Barth, Markus (2024). Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T. Magnetic Resonance in Medicine, 92 (3), 997-1010. doi: 10.1002/mrm.30101

Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T

2024

Journal Article

Modular GAN: positron emission tomography image reconstruction using two generative adversarial networks

Vashistha, Rajat, Vegh, Viktor, Moradi, Hamed, Hammond, Amanda, O’Brien, Kieran and Reutens, David (2024). Modular GAN: positron emission tomography image reconstruction using two generative adversarial networks. Frontiers in Radiology, 4 1466498, 1-16. doi: 10.3389/fradi.2024.1466498

Modular GAN: positron emission tomography image reconstruction using two generative adversarial networks

2024

Journal Article

Evaluation of deep‐learning TSE images in clinical musculoskeletal imaging

Vashistha, Rajat, Almuqbel, Mustafa M, Palmer, Nick J, Keenan, Ross J, Gilbert, Kevin, Wells, Scott, Lynch, Andrew, Li, Andrew, Kingston‐Smith, Stephen, Melzer, Tracy R, Koerzdoerfer, Gregor and O'Brien, Kieran (2024). Evaluation of deep‐learning TSE images in clinical musculoskeletal imaging. Journal of Medical Imaging and Radiation Oncology, 68 (5), 556-563. doi: 10.1111/1754-9485.13714

Evaluation of deep‐learning TSE images in clinical musculoskeletal imaging

2024

Journal Article

B1+ inhomogeneity mitigation for diffusion weighted MRI at 7T using TR‐FOCI pulses

Abbasi‐Rad, Shahrokh, Cloos, Martijn A., Jin, Jin, O'Brien, Kieran and Barth, Markus (2024). B1+ inhomogeneity mitigation for diffusion weighted MRI at 7T using TR‐FOCI pulses. Magnetic Resonance in Medicine, 91 (6), 2508-2518. doi: 10.1002/mrm.30024

B1+ inhomogeneity mitigation for diffusion weighted MRI at 7T using TR‐FOCI pulses

2024

Journal Article

Automated extraction of the arterial input function from brain images for parametric PET studies

Moradi, Hamed, Vashistha, Rajat, Ghosh, Soumen, O’Brien, Kieran, Hammond, Amanda, Rominger, Axel, Sari, Hasan, Shi, Kuangyu, Vegh, Viktor and Reutens, David (2024). Automated extraction of the arterial input function from brain images for parametric PET studies. EJNMMI Research, 14 (1) 33, 1-18. doi: 10.1186/s13550-024-01100-x

Automated extraction of the arterial input function from brain images for parametric PET studies

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

Conference Publication

Fast, High-resolution Whole Brain SWI and QSM with CAIPIRINHA 3D-EPI and Deep Learning Reconstruction

Jin, Jin, Nickel, Dominik, Pfeuffer, Josef, Tourell, Monique, Stewart, Ashley, Bollmann, Steffen, Bollmann, Saskia, Barth, Markus and O‘Brien, Kieran (2024). Fast, High-resolution Whole Brain SWI and QSM with CAIPIRINHA 3D-EPI and Deep Learning Reconstruction. 2024 ISMRM & ISMRT Annual Meeting, Singapore, 4-9 May 2024. Concord, CA United States: ISMRM. doi: 10.58530/2024/2822

Fast, High-resolution Whole Brain SWI and QSM with CAIPIRINHA 3D-EPI and Deep Learning Reconstruction

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

Overcoming challenges of quantitative susceptibility mapping in moderate-to-severe TBI patients

D., Juan Domínguez, Stewart, Ashley, Burmester, Alex, Akhlaghi, Hamed, O’Brien, Kieran, Bollmann, Steffen and Caeyenberghs, Karen (2024). Overcoming challenges of quantitative susceptibility mapping in moderate-to-severe TBI patients. 2024 ISMRM & ISMRT Annual Meeting, Singapore, 4-9 May 2024. Concord, CA United States: ISMRM. doi: 10.58530/2024/1622

Overcoming challenges of quantitative susceptibility mapping in moderate-to-severe TBI patients

2023

Other Outputs

Deep-learning-enabled differentiation between intraprostatic gold fiducial markers and calcification in quantitative susceptibility mapping

Stewart, Ashley Wilton, Goodwin, Jonathan, Richardson, Matthew, Robinson, Simon Daniel, O’Brien, Kieran, Jin, Jin, Barth, Markus and Bollmann, Steffen (2023). Deep-learning-enabled differentiation between intraprostatic gold fiducial markers and calcification in quantitative susceptibility mapping.

Deep-learning-enabled differentiation between intraprostatic gold fiducial markers and calcification in quantitative susceptibility mapping

2023

Journal Article

Improved dynamic distortion correction for fMRI using single‐echo EPI and a readout‐reversed first image (REFILL)

Robinson, Simon Daniel, Bachrata, Beata, Eckstein, Korbinian, Bollmann, Saskia, Bollmann, Steffen, Dymerska, Barbara, Hodono, Shota, Cloos, Martijn, Tourell, Monique, Jin, Jin, O'Brien, Kieran, Reutens, David C., Trattnig, Siegfried, Enzinger, Christian and Barth, Markus (2023). Improved dynamic distortion correction for fMRI using single‐echo EPI and a readout‐reversed first image (REFILL). Human Brain Mapping, 44 (15), 5095-5112. doi: 10.1002/hbm.26440

Improved dynamic distortion correction for fMRI using single‐echo EPI and a readout‐reversed first image (REFILL)

2023

Journal Article

NeXtQSM—A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data

Cognolato, Francesco, O’Brien, Kieran, Jin, Jin, Robinson, Simon, Laun, Frederik B., Barth, Markus and Bollmann, Steffen (2023). NeXtQSM—A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data. Medical Image Analysis, 84 102700, 102700. doi: 10.1016/j.media.2022.102700

NeXtQSM—A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data

2023

Conference Publication

Evaluation of the REFILL dynamic distortion correction method for fMRI

Robinson, Simon, Bachrata, Beata, Eckstein, Korbinian, Dymerska, Barbara, Bollmann, Saskia, Bollmann, Steffen, Hodono, Shota, Cloos, Martijn, Tourell, Monique, Jin, Jin, O'Brien, Kieran, Reutens, David, Trattnig, Siegfried, Enzinger, Christian and Barth, Markus (2023). Evaluation of the REFILL dynamic distortion correction method for fMRI. 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: 10.58530/2022/2807

Evaluation of the REFILL dynamic distortion correction method for fMRI

2023

Conference Publication

Development of a Quantitative Susceptibility Mapping (QSM) phantom for validation of acquisition strategies and post-processing tools at 3 T

Hooper, Padriac, Tourell, Monique, O'Brien, Kieran, Jin, Jin, Robinson, Simon and Barth, Markus (2023). Development of a Quantitative Susceptibility Mapping (QSM) phantom for validation of acquisition strategies and post-processing tools at 3 T. Joint Annual Meeting ISMRM-ESMRMB and ISMRT 31st Annual Meeting, London, United Kingdom, 7-12 May 2022. Berkeley, CA United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2022/1983

Development of a Quantitative Susceptibility Mapping (QSM) phantom for validation of acquisition strategies and post-processing tools at 3 T

2022

Journal Article

The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field

Coorey, Genevieve, Figtree, Gemma A., Fletcher, David F., Snelson, Victoria J., Vernon, Stephen Thomas, Winlaw, David, Grieve, Stuart M., McEwan, Alistair, Yang, Jean Yee Hwa, Qian, Pierre, O’Brien, Kieran, Orchard, Jessica, Kim, Jinman, Patel, Sanjay and Redfern, Julie (2022). The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field. npj Digital Medicine, 5 (1) 126, 1-12. doi: 10.1038/s41746-022-00640-7

The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field

Past funding

  • 2014 - 2018
    Verifying the safety and image quality of metallic implants at 7T using single and parallel transmit systems
    Siemens Ltd
    Open grant

Availability

Dr Kieran O'Brien is:
Available for supervision

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Supervision history

Current supervision

Completed supervision

Enquiries

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