MRI Together
Global workshop on open, reproducible, and inclusive MR research
Day 1: December 3th
Bridging the educational gap (15:00 - 17:00 UTC)
MRI Together: Opening MRI Together 2024
Jonathan Martin: Disseminating Open-Source Software Tools for Robust, Smart, and Accessible MRI
In this talk I will discuss applications of AI techniques to preclinical and low-field MRI, and discuss open-source software packages and publishing methods. I will also review my own experiences in building open-source low field scanners.
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New Kids on the Block - open science in emerging MR applications (embodying open MRI) (21:00-23:00 UTC)
Peder Larson: Open-source software tools for emerging applications of hyperpolarized MRI and lung MRI
In this talk I will share my personal experience in developing open-source software tools in the areas of hyperpolarized carbon-13 MRI and for lung MRI. These are emerging areas being developed by relatively small communities of researchers, which is a unique opportunity to use open science practices to better leverage limited resources.
David Mummy: Raising a Standard: A Framework for 129Xe MRI Multi-Site Data Sharing and Analysis
Hyperpolarized Xenon MRI is a rapidly growing technique for assessing pulmonary gas exchange. This talk will describe efforts by the Xenon MRI community to establish standards for raw data sharing and analysis in order to directly compare imaging results across sites and to conduct multi-site clinical trials.
Charles McGrath: The Road to developing the CMRsim framework: more than just MR physics
The first part of the talk will give a brief introduction to CMRsim as well as the specific requirements of cardiac MR simulation that motivated the development. The remainder will focus on the lessons learned along the way pertaining to open-source development as well as the current and future obstacles for open-source MR simulation.
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Day 2: December 4th
The funding landscape for open source projects (3:00 - 5:00 UTC)
Hai-Yang Geng: An Introduction to Computational Psychiatry: from research to application
An interdisciplinary education system is being to train computational psychiatry experts who can apply quantitative methods to clinical problems. We envision an integrated computational psychiatry system that offers AI-aided, evidence-based assessment and intervention tools through digital health platforms, connecting researchers, clinicians, and patients to enhance online mental health services. The combination of big data from wearable devices and advanced AI technologies will advance precision psychiatry, enabling early risk screening and the development of targeted individualized treatments.
Lu-Lu Jiang: Promoting Open Data Best Practices from a Data Repository Perspective
Open data plays a crucial role in enhancing research transparency, improving research reproducibility, and advancing scientific progress. This report uses the case study of Science Data Bank, a public data repository, to illustrate how data repositories serve as a bridge connecting scientists with data policies, data standards, and data dissemination in promoting open data.
Aswin Narayanan: Development journey of the Neurodesk platform
A development journey of the Neurodesk platform and software project. The talk what the project is about, how it came to be, funding roadmap, challenges, breakthroughs and solutions along the way and possible future plans.
Jon-Fredrik Nielsen: Funding and sustaining Pulseq projects and tool development: Reaching critical mass and leveraging vendor synergies
Open source tool development is crucial for reproducible science, but may not always align with existing funding mechanisms and vendor incentives. I’ll discuss our experience obtaining funding to develop and disseminate a vendor-agnostic functional MRI protocol based on Pulseq, with an emphasis on building connections with both the MRI research community and the vendors.
Transferable open MRI skills: from academia to industry (9:00 - 11:00 UTC)
Ira Ktena: Developing health AI models that are safe for the world
This talk will cover considerations that arise when transitioning from developing ML models for narrow research applications to models that scale and perform well across geographies and populations. The talk will also cover why industry researchers should engage with academics to ensure reproducibility and build trust in new technologies.
Kevin Aquino: Transferrable skills in the startup space
While the transition to “industry” may appear daunting, the startup world can offer a sense of familiarity to those wanting to branch away from academia. In this talk, I will share my journey and some pleasant surprises along the way.
Han Peng: Hopping through domain walls, a physicist’s perspective
Han will share his journey of navigating through the field of physics and AI, and his personal experience in work and life in academia and industrial positions as an international scholar. Fun fact: Han started his first industrial job during his 21-day stay in a quarantine hotel in Beijing in 2021.
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Reproducibility crisis revisited (17:00-19:00 UTC)
Zhi-Yi Chen: Population diversity flaw in the AI-empowered neuroimaging studies and generalization failure
Though the immense potentials and unprecedented increases in the AI-empowered neuroimaging-based studies, particularly in diagnostics, global population diversity in these computational models are highly underrepresented. Embracing AI techniques in the neuroimaging studies should be greatly welcomed, but as a result, sampling inequalities from AI model training and testing biases from AI model deployments substantially limited their real-world practices and ensuing benefits.
Stephanie Noble: Mapping the Landscape of Effect Sizes in fMRI: Insights from Large Publicly Available Dataset
Understanding what range of effect sizes are “typical” for fMRI studies is essential for better study planning and interpretation of results, especially given recent concerns about reproducibility and statistical power in fMRI research. Here, we leverage large, publicly available datasets to benchmark expected effect sizes for “typical” studies and introduce a web app for exploring these effects. We emphasize the need to plan for small effect sizes and discuss paths forward, including our next steps developing an empirical power calculator web app.
Martin Hebart: The THINGS initiative: Improving the generalizability of research findings in vision and semantics across studies, methods, and domains
Visual and semantic processing has been studied using both hypothesis-driven and data-driven approaches. However, the generalizability of research findings always depends on the selection of stimulus materials, and with inconsistent use of materials, it has been challenging to directly relate research findings across studies, research methods (e.g., behaviour, fMRI, electrophysiology), and domains (e.g., humans, animal models, artificial intelligence). To overcome these challenges, we have introduced the THINGS initiative, which is a global initiative of researchers to collect and share datasets all based on the THINGS database of object concepts and images. In this talk, I will highlight the opportunities afforded by this initiative, introduce available datasets, and highlight research findings that have underscored the value of this approach.
Panel discussion
Cutting-edge MRI toolbox exhibition: Live demos and interactive sessions (Americas) (23:00-01:00 UTC)
Thomas Küstner: MERLIN - Machine Enhanced Reconstruction Learning and Interpretation Networks
Machine Learning (ML) methods have evolved tremendously during the last decade with a number of backends supporting the development. However, support for high-dimensional and complex-valued data processing is often limited. Therefore, we developed a Machine Enhanced Reconstruction Learning and Interpretation Networks (MERLIN) framework that seamlessly integrates with existing ML solutions (Tensorflow/Keras and Pytorch) and complements them by high-dimensional, complex-valued and MR-specific operators, layers, and data pipelines.
Abood Bdaiwi: 129Xe Image Processing Pipeline (XIPline): An Open-Source, Graphical User Interface Application for the Analysis of Hyperpolarized 129Xe MRI
Hyperpolarized 129Xe MRI is an emerging tool for assessing regional lung microstructure and function. This talk will introduce XIPline, an open-source, user-friendly software developed for standardizing the analysis of 129Xe MRI data, covering ventilation, diffusion, and gas exchange imaging. Ongoing efforts to streamline processing and increase research adoption will be highlighted.
Alexandre D’Astous: Hands on with Shimming Toolbox
MIRTorch, developed at the University of Michigan, focuses on reimplementing basic model-based MRI reconstruction in PyTorch. The project enables researchers to run fast reconstruction algorithms on GPUs, easily prototype new reconstruction methods, and explore innovative directions through differentiable programming.
Guanhua Wang: MIRTorch: Ultrafast and Differentiable MRI Reconstruction Using PyTorch
MIRTorch, developed at the University of Michigan, focuses on reimplementing basic model-based MRI reconstruction in PyTorch. The project enables researchers to run fast reconstruction algorithms on GPUs, easily prototype new reconstruction methods, and explore innovative directions through differentiable programming.
Day 3: December 5th
Open science - Standards for sharing data and code (Asia/Australia) (05:00 - 07:00 UTC)
Steffen Bollmann: Neurodesk – reproducible Neuroimaging for everyone, anywhere
Neurodesk is a platform for making reproducible Neuroimaging accessible to everyone. In this talk, he will give a quick overview of what Neurodesk is, how it works, how it supports open data analyses and I will briefly show our latest developments on running Neurodesk containers on the scanner through Open Recon.
Eberechi Wogu: Driving FAIR Brain Data in Africa: Challenges and Opportunities.
This talk highlights the experiences of researchers from the African Brain Data Network whose goal is to make African brain data FAIR. It also includes their critical observations as they collected, curated, and shared the first African brain imaging dataset. These observations include the understanding of the importance of FAIR African brain data, the challenges FAIR brain data faces in Africa and the opportunities for growth.
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Tools of the trade - tutorials and essential open science software (east coast USA/Europe) (11:00 - 13:00 UTC)
Korbinian Eckstein: Using VS code effectively and cool extensions
In this talk, I will share practical tips for effectively using Visual Studio Code, a versatile code editor that can greatly enhance productivity. I will highlight several useful extensions (git, AI autocomplete, image viewer, formatting, …). Attendees will learn how to customize the environment to suit their specific needs and might find some new favourite extensions.
Thuy Dao: Data standardisation using BIDS on Neurodesk
This talk will cover best practices for open science in MR research, highlighting the Brain Imaging Data Structure (BIDS) as a standard for organizing neuroimaging data. We’ll demonstrate how to connect data to Neurodesk, an open platform that improves tool accessibility and reproducibility, and convert it to BIDS format using various tools within Neurodesk.
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At second sight - open science projects that succeeded at their own pace (19:00-21:00 UTC)
Fernanda Hansen: Connecting theoretical models to brain structure: a physical study of cortical gyrification
Cortical folding has been of great interest in recent years, but there is a missing link to connect theoretical models to evidence. In this talk, we show what we’ve done so far and how Open Science approaches are important to accomplish more.
Ting Xu: Leveraging Data Sharing in Nonhuman Primates to Chart Brain Development in Macaques
Nonhuman primates (NHPs) serve as essential models in translational neuroscience. However, the small sample sizes in many NHP imaging studies limit cross-species comparisons with large-scale human brain data. In this presentation, I will introduce the Macaque Charts project, which uses over 1,000 MRI datasets from the PRIMatE Data Exchange (PRIME-DE) consortium to map lifespan brain trajectories in macaques.
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Day 4 December 6th
Collaborative coding towards more impactful solutions (1:00 - 3:00 UTC)
Chris Rorden: NiiVue: Modular neuroimaging visualization based on web technologies
Visualization plays a crucial role in neuroimaging acquisition, processing, inference and dissemination. The AFNI, FSL and FreeSurfer have created competing desktop tools, making it hard for users to transfer skills and data between these frameworks. We have harnessed the collective wisdom of these teams to develop NiiVue using web technologies. This allows a zero-footprint tool that works regardless of device (computer, phone, tablet), operating system, hardware or framework. In addition to traditional desktop use, this software enables innovative edge and cloud-based applications.
Ashley Stewart: Building Robust Software with Automation, Containers, and Open Standards
Transparency and reproducibility in scientific software development are critical to open science. This talk will discuss strategies for automatically testing and evaluating workflows using GitHub Actions, software containers, and open standards such as the Brain Imaging Data Structure (BIDS). The continuously integrated reconstruction challenge for Quantitative Susceptibility Mapping (QSM-CI) will be presented as an example of how a community-driven project can use these standards to unlock new possibilities in neuroimaging investigations that drive innovation.
Mary Miedema: Meeting contributors where they’re at: case studies from Physiopy in making code contribution accessible
In this talk, I will discuss a range of strategies that have helped new contributors to advance Physiopy’s code base, including the organization of codesprints, participation in Google’s Summer of Code, and the ongoing compilation of contribution standards and other community coding knowledge.
MRI Together 2024 Highlights (6:00 - 8:00 UTC)
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Sustainable volunteering (13:00 - 15:00 UTC)
Chuan-Peng Hu: Promoting Open Science in a Developing Country
In the past seven years, several Chinese early-career researchers and I have been promoting open science among the Chinese-speaking community by initiating a grassroots network — the Chinese Open Science Network (COSN, Jin et al., 2023). In this talk, I will share our stories and the lessons we have learned.
Sina Mansour: Open Science Volunteering and Academia: Navigating the Challenges and Rewards
In this session, I’ll share my journey as a researcher passionate about open science initiatives, highlighting the meaningful connections between open science and academia through aspects like open code, open data, reproducibility, and transparency. I’ll discuss the ups and downs I’ve encountered along the way, offering a candid view of the benefits and challenges of advocating for open science in an academic environment. This talk aims to offer practical insights that can assist attendees in navigating their own paths in this rewarding yet complex landscape.
Silvia Maier: Steering your life and projects wisely – a neuroscience-informed perspective
Throughout my professional life, volunteering side projects have been a part of my work portfolio. As a former neuroscientist studying self-control, stress and resilience, my insights from my research together with my growing project management practice helped me develop my own take on how to run myself and my work in a sustainable fashion so I could bring meaningful complex projects to fruition. With a nod to the realities and insights of cognitive neuroscience on self-control and stress, I am happy to share some of my takeaways and steps on how to practically approach and steer your course while handling a demanding project and life portfolio that meets not only your ambition, but also your needs when it comes to nurturing your soul and health.