Overview
Background
Dr Steffen Bollmann joined UQ’s School of Electrical Imaging and Computer Science in 2020 where he leads the Computational Imaging Group. The Group is developing computational methods to extract clinical and biological insights from magnetic resonance imaging (MRI) data. The aim is to make cutting-edge algorithms and tools available to a wide range of clinicians and researchers. This will enable better images, faster reconstruction times and the efficient extraction of clinical information to ensure a better understanding of a range of diseases. Dr Bollmann was appointed Artificial Intelligence (AI) lead for imaging at UQ’s Queensland Digital Health Centre (QDHeC) in 2023.
His research expertise is in quantitative susceptibility mapping, image segmentation and software applications to help researchers and clinicians access data and algorithms.
Dr Bollmann completed his PhD on multimodal imaging at the University Children’s Hospital and Swiss Federal Institute of Technology (ETH) Zurich, Switzerland.
In 2014 he joined the Centre for Advanced Imaging at UQ as a National Imaging Facility Fellow, where he pioneered the application of deep learning methods for quantitative imaging techniques, in particular Quantitative Susceptibility Mapping.
In 2019 he joined the Siemens Healthineers collaborations team at the MGH Martinos Center in Boston on a one-year industry exchange where he worked on the translation of fast imaging techniques into clinical applications.
Availability
- Dr Steffen Bollmann is:
- Available for supervision
Fields of research
Research interests
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Reproducible Research Software
Developing software to enable reproducible neuroimaging, such as www.Neurodesk.org
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Computational Imaging
Developing tools to make computational algorithms for medical imaging more accessible and robust.
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Image Segmentation
Developing new methods to segment medical imaging data to extract quantitative information.
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Quantitative Susceptibility Mapping
Developing new methods to increase the robustness of processing quantitative susceptibility mapping.
Research impacts
Strong industry collaborations to bring research algorithms into applications such as Quantitative Susceptibility Mapping with industry partner Siemens Healthineers and the Neurodesk project with industry partner Oracle Cloud.
Further information is available at www.mri.sbollmann.net and regular research updates can be found on linkedin (https://www.linkedin.com/in/steffen-bollmann-00725097/) mastodon (https://masto.ai/@Sbollmann_MRI) and twitter/X (https://twitter.com/sbollmann_mri)
Works
Search Professor Steffen Bollmann’s works on UQ eSpace
2024
Journal Article
Building a Comprehensive Toolkit for Human Visual Cortex Parcellation
Ribeiro, Fernanda L., Bambridge-Lozan, Torin, Benson, Noah C., Schwarzkopf, D. Samuel, Puckett, Alexander M. and Bollmann, Steffen (2024). Building a Comprehensive Toolkit for Human Visual Cortex Parcellation. Journal of Vision, 24 (10), 691. doi: 10.1167/jov.24.10.691
2024
Journal Article
VesselBoost: a Python toolbox for small blood vessel segmentation in human magnetic resonance angiography data
Xu, Marshall, Ribeiro, Fernanda L., Barth, Markus, Bernier, Michaël, Bollmann, Steffen, Chatterjee, Soumick, Cognolato, Francesco, Gulban, Omer F., Itkyal, Vaibhavi, Liu, Siyu, Mattern, Hendrik, Polimeni, Jonathan R., Shaw, Thomas B., Speck, Oliver and Bollmann, Saskia (2024). VesselBoost: a Python toolbox for small blood vessel segmentation in human magnetic resonance angiography data. Aperture Neuro, 4, 1-13. doi: 10.52294/001c.123217
2024
Journal Article
Large‐scale analysis of structural brain asymmetries during neurodevelopment: Associations with age and sex in 4265 children and adolescents
Kurth, F., Schijven, D., van den Heuvel, O. A., Hoogman, M., van Rooij, D., Stein, D. J., Buitelaar, J. K., Bölte, S., Auzias, G., Kushki, A., Venkatasubramanian, G., Rubia, K., Bollmann, S., Isaksson, J., Jaspers‐Fayer, F., Marsh, R., Batistuzzo, M. C., Arnold, P. D., Bressan, R. A., Stewart, S. E., Gruner, P., Sorensen, L., Pan, P. M., Silk, T. J., Gur, R. C., Cubillo, A. I., Haavik, J., O'Gorman Tuura, R. L., Hartman, C. A. ... Luders, E. (2024). Large‐scale analysis of structural brain asymmetries during neurodevelopment: Associations with age and sex in 4265 children and adolescents. Human Brain Mapping, 45 (11) e26754, e26754. doi: 10.1002/hbm.26754
2024
Conference Publication
Aberrations in the Ventral Tegmental Area predict depression severity in the general population
Khalife, Sarah, Oestreich, Lena, Bollmann, Steffen and Zalesky, Andrew (2024). Aberrations in the Ventral Tegmental Area predict depression severity in the general population. Organization for Human Brain Mapping, Seoul, South Korea, 23-27 June 2024.
2024
Journal Article
Author Correction: brainlife.io: a decentralized and open-source cloud platform to support neuroscience research
Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj ... Pestilli, Franco (2024). Author Correction: brainlife.io: a decentralized and open-source cloud platform to support neuroscience research. Nature Methods, 21 (6), 1131-1131. doi: 10.1038/s41592-024-02296-5
2024
Journal Article
Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging
Renton, Angela I., Dao, Thuy T., Johnstone, Tom, Civier, Oren, Sullivan, Ryan P., White, David J., Lyons, Paris, Slade, Benjamin M., Abbott, David F., Amos, Toluwani J., Bollmann, Saskia, Botting, Andy, Campbell, Megan E. J., Chang, Jeryn, Close, Thomas G., Dörig, Monika, Eckstein, Korbinian, Egan, Gary F., Evas, Stefanie, Flandin, Guillaume, Garner, Kelly G., Garrido, Marta I., Ghosh, Satrajit S., Grignard, Martin, Halchenko, Yaroslav O., Hannan, Anthony J., Heinsfeld, Anibal S., Huber, Laurentius, Hughes, Matthew E. ... Bollmann, Steffen (2024). Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging. Nature Methods, 21 (2), 804-808. doi: 10.1038/s41592-023-02145-x
2024
Journal Article
Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging
Renton, Angela I., Dao, Thuy T., Johnstone, Tom, Civier, Oren, Sullivan, Ryan P., White, David J., Lyons, Paris, Slade, Benjamin M., Abbott, David F., Amos, Toluwani J., Bollmann, Saskia, Botting, Andy, Campbell, Megan E. J., Chang, Jeryn, Close, Thomas G., Dörig, Monika, Eckstein, Korbinian, Egan, Gary F., Evas, Stefanie, Flandin, Guillaume, Garner, Kelly G., Garrido, Marta I., Ghosh, Satrajit S., Grignard, Martin, Halchenko, Yaroslav O., Hannan, Anthony J., Heinsfeld, Anibal S., Huber, Laurentius, Hughes, Matthew E. ... Bollmann, Steffen (2024). Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging. Nature Methods, 21 (5), 804-808. doi: 10.1038/s41592-023-02145-x
2024
Journal Article
brainlife.io: a decentralized and open-source cloud platform to support neuroscience research
Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj ... Pestilli, Franco (2024). brainlife.io: a decentralized and open-source cloud platform to support neuroscience research. Nature Methods, 21 (5), 809-813. doi: 10.1038/s41592-024-02237-2
2024
Journal Article
Adiposity associates with lower plasma resolvin E1 (Rve1): a population study
Barden, Anne, Shinde, Sujata, Beilin, Lawrence J., Phillips, Michael, Adams, Leon, Bollmann, Steffen and Mori, Trevor A. (2024). Adiposity associates with lower plasma resolvin E1 (Rve1): a population study. International Journal of Obesity, 48 (5), 725-732. doi: 10.1038/s41366-024-01482-x
2024
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 (2024). Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level. Zeitschrift für Medizinische Physik. doi: 10.1016/j.zemedi.2024.01.001
2024
Conference Publication
Computationally efficient multi-echo QSM
Eckstein, Korbinian, Dao, Thanh, Stewart, Ashley, Robinson, Simon, Barth, Markus and Bollmann, Steffen (2024). Computationally efficient multi-echo QSM. 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: 10.58530/2023/4184
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
2023
Conference Publication
Developing a secure, browser-based and interactive image segmentation system for medical images
Dao, Thuy, Rorden, Chris, Eckstein, Korbinian, Haehn, Daniel, Varade, Shruti and Bollmann, Steffen (2023). Developing a secure, browser-based and interactive image segmentation system for medical images. International Society for Magnetic Resonance in Medicine ANZ Chapter, Brisbane, QLD, Australia, 30 November - 1 December 2023.
2023
Journal Article
Super-resolution QSM in little or No Additional Time for Imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes
Bachrata, Beata, Bollmann, Steffen, Jin, Jin, Tourell, Monique, Dal-Bianco, Assunta, Trattnig, Siegfried, Barth, Markus, Ropele, Stefan, Enzinger, Christian and Robinson, Simon Daniel (2023). Super-resolution QSM in little or No Additional Time for Imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes. NeuroImage, 283 120419, 1-17. doi: 10.1016/j.neuroimage.2023.120419
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.
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
2023
Journal Article
Variability of visual field maps in human early extrastriate cortex challenges the canonical model of organization of V2 and V3
Lenita Ribeiro, Fernanda, York, Ashley, Zavitz, Elizabeth, Bollmann, Steffen, Rosa, Marcello G.P. and Puckett, Alexander (2023). Variability of visual field maps in human early extrastriate cortex challenges the canonical model of organization of V2 and V3. eLife e86439. doi: 10.7554/eLife.86439
2023
Journal Article
Variability of visual field maps in human early extrastriate cortex challenges the canonical model of organization of V2 and V3
Ribeiro, Fernanda Lenita, York, Ashley, Zavitz, Elizabeth, Bollmann, Steffen, Rosa, Marcello GP and Puckett, Alexander (2023). Variability of visual field maps in human early extrastriate cortex challenges the canonical model of organization of V2 and V3. eLife, 12. doi: 10.7554/elife.86439
2023
Conference Publication
Investigating the computational reproducibility of Neurodesk
Dao, Thuy, Renton, Angela, Narayanan, Aswin, Barth, Markus and Bollmann, Steffen (2023). Investigating the computational reproducibility of Neurodesk. International Society for Magnetic Resonance in Medicine, Toronto, ON, Canada, 3-8 June 2023.
2023
Conference Publication
Proceedings of the OHBM Brainhack 2021
Nikolaidis, Aki, Manchini, Matteo, Auer, Tibor, L. Bottenhorn, Katherine, Alonso-Ortiz, Eva, Gonzalez-Escamilla, Gabriel, Valk, Sofie, Glatard, Tristan, Selim Atay, Melvin, M.M. Bayer, Johanna, Bijsterbosch, Janine, Algermissen, Johannes, Beck, Natacha, Bermudez, Patrick, Poyraz Bilgin, Isil, Bollmann, Steffen, Bradley, Claire, E.J. Campbell, Megan, Caron, Bryan, Civier, Oren, Pedro Coelho, Luis, El Damaty, Shady, Das, Samir, Dugré, Mathieu, Earl, Eric, Evas, Stefanie, Lopes Fischer, Nastassja, Fu Yap, De, G. Garner, Kelly ... P. Zwiers, Marcel (2023). Proceedings of the OHBM Brainhack 2021. OHBM Brainhack 2021, Online, 16-18 June 2021. Organization for Human Brain Mapping. doi: 10.52294/258801b4-a9a9-4d30-a468-c43646391211
Funding
Current funding
Past funding
Supervision
Availability
- Dr Steffen Bollmann is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Available projects
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Reproducible Neuroimaging Framework NeuroDesk
This project provides a reproducible neuroimaging data processing platform based on software containers (docker and singularity). More information about this project can be found in the Nature Methods article: https://rdcu.be/dQJjq
The candidate will be able to learn about container technology and add new features to the platform, like the support of GPUs for deep learning applications, the support for M1/Arm processors by using muli-architecture builds, develop cloud deployment patterns using Kubernetes, build large language models to support users in programming neuroimaging applications and many more.
Supervision history
Current supervision
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Doctor Philosophy
Robust Deep learning for Quantitative Susceptibility Mapping
Principal Advisor
Other advisors: Dr Fernanda Lenita Ribeiro
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Doctor Philosophy
Computational Medical Imaging
Principal Advisor
Other advisors: Dr Fernanda Lenita Ribeiro, Mr Aswin Narayanan
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Doctor Philosophy
Structure-function brain network dynamics in post-stroke depression
Associate Advisor
Other advisors: Dr Lena Oestreich
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Doctor Philosophy
Development of a deep learning framework for multi-modal medical imaging
Associate Advisor
Other advisors: Professor Markus Barth
Completed supervision
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2023
Master Philosophy
Solving Quantitative Susceptibility Mapping using Deep Learning
Principal Advisor
Other advisors: Professor Markus Barth
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2023
Doctor Philosophy
Automated Quantitative Susceptibility Mapping for Clinical Applications
Principal Advisor
Other advisors: Professor Markus Barth, Dr Monique Tourell
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2021
Doctor Philosophy
Computational in vivo Tissue Characterisation for Multi-Contrast High-Resolution Magnetic Resonance Imaging Data
Principal Advisor
Other advisors: Professor Markus Barth
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2024
Doctor Philosophy
Magnetostatic Modelling based on Deep Learning
Associate Advisor
Other advisors: Dr Michael Bermingham, Professor Matthew Dargusch
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2021
Doctor Philosophy
Sequence Development to Improve Image Quality for T2- and Diffusion Weighted Imaging at 7T
Associate Advisor
Other advisors: Associate Professor Martijn Cloos, Professor Markus Barth
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2020
Doctor Philosophy
MR signal modelling approaches to characterise tissue microstructure in in-vivo human brain
Associate Advisor
Other advisors: Dr Viktor Vegh, Professor Markus Barth
Media
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