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Solving MRI inversion problems for quantitative multi-parameter estimation
Topic: Inversion problems, regularization, bSSFP, MRI simulations, data processing and analysis, complex systems.
Who: Students with a background in mathematics, computer science, physics, electrical or bio(medical) engineering. Everyone who is interested in new and creative mathematical models and solutions, regularization, computer simulations and parameter estimation on real experimental data.
Background: In quantitative MRI the dynamics of a complex physical system is described by the combination of a set of physical equations leading to a certain kind of quantitative model or quantitative map. Those respective models/maps are used for the quantification of e.g. water-fat fractions or T1- and T2-time. By trying to map acquired/simulated data to the quantitative parameter of interest, inversion problems are frequently encountered. Depending on the problem, inversions can be challenging to solve. The challenge can either originate on the sparsity of acquired data or also on the mathematical model itself. The quantification of multi-Compartment systems in MRI exhibits a lot of inversion operations, where some problems arise as ambiguities or so called “ill-posed problems”. Sometimes it is possible to find solutions of the inversion by constraining the system to boundary conditions, by reducing the complexity or dimensionality of the model or bring it in another mathematical formulation. Some of those problems are not well understood yet and their solution is key for a robust quantification of multi-compartment systems in MRI.
Project: In this project, we aim to first identify a system with known dynamics, and then develop a solution for the identified system. The prospective student will investigate inversion problems arising in parameter quantification in multi-compartment systems, like water and fat, with special focus on the bSSFP-sequence. We will investigate whether a problem can be solved analytically/numerically by an unambiguous mathematical representation or develop a regularized inverse problem-solving technique. Elaborated solutions will be tested in simulations (Bloch-Simulation) and on real experimental data.
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Latest posts
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PhD and Postdoctoral position on innovating MRI for the quantification of liver disease biomarkers
We are looking for two motivated researchers who are interested in working at the intersection of engineering, physics, and medicine. The candidates will join a growing and dynamic team to push MRI further! The advertised positions are funded by the SNSF for the project “Advanced lipid-insensitive MRI relaxometry for unbiased noninvasive characterization of the entire […]
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SNSF Project Grant awarded to Prof. Jessica Bastiaansen
Jessica Bastiaansen was awarded an SNSF project grant entitled “Advanced lipid-insensitive MRI relaxometry for unbiased noninvasive characterization of the entire human liver” Significant shortcomings exist in the current imaging technology for assessing biomarkers of liver disease such as fibrosis. Current methods are not designed for the liver. Hence, they face challenges due to the presence […]
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CAIM Fellowship for Dr. Eva Peper
Dr. Eva Peper received the prestigious CAIM Fellowship from the University of Bern. The project is entitled “AI Acceleration of 3D Cardiac bSSFP MRI” and will start in summer 2024. Stay tuned for positions opening up!
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Welcome Yves
Yves is a student in the MSc program in Biomedical Engineering at the University of Bern. He will work with us on quantitative susceptibility mapping at 7T, together with Berk. We are excited to have you on the team!
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Welcome Guillaume, Janick, and Matteo
Three new Biomedical Engineering Master students have joined the QIS lab. They will be working on biomarker mapping in the human brain, fat-free relaxometry of the human liver, and free-breathing cardiac image reconstructions. Welcome to the team!
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Welcome to Kelly Bonzon and Melina Gilsing
Two new Biomedical Engineering Master students have joined the QIS lab. They will be working on the implementation of open source pulse sequences and AI tools for advanced processing and reconstruction of MRI data. Welcome to the team!
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MR-eye 2.0 – SNSF Project on novel imaging tools for the human eye
Prof. Benedetta Franceschiello was awarded an SNSF grant related to the Health Research and Wellbeing UAS and UTE call, entitled: 2.0 MR-Eye: Towards a consensual Magnetic resonance Imaging protocol of the Human Eye At the QIS lab we are partners on this project, which will be conducted at the 7T scanner at the Translational Imaging […]
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Jessica Bastiaansen teaches in the ESMRMB School of MRI about Advanced and Applied MRI Principles
Jessica gives a lecture on the topic “Fat suppression and Introduction to Quantitative Imaging”, which is part of the Practical MR Physics course organized by the ESMRMB School of MRI. The lecture series is composed of different topics geared around the field of magnetic resonance imaging. More information can be found on the following link.
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Jessica Bastiaansen joins the Annual Meeting Program Committee (AMPC) of the ISMRM
Jessica was invited to serve on the Annual Meeting Programming Committee (AMPC) of the International Society for Magnetic Resonance in Medicine (ISMRM). “It is a true honour to be asked to be part of the AMPC, and I look forward to contribute to the organization of the next three ISMRM meetings!”. The annual meeting attracts […]
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Dr. Rahel Heule presented about asymmetries in the brain at 9.4T
Dr Rahel Heule from the Max Planck Institute in Tuebingen and the children’s hospital in Zuerich visited our imaging center in Bern. She gave a seminar entitled “Asymmetries in the Brain: A Methodological Exploration of bSSFP MRI in Neuroimaging at 3T and 9.4T“. Our belief in bSSFP methods to uncover novel biomarkers have only been […]
