Conditional Generative Models for Contrast-Enhanced Synthesis of T1W and T1 Maps in Brain MRI
by Fabian Altekrüger, Moritz Piening, Gabriele Steidl, Elke Hattingen, Eike Steidl
Year:
2024
Abstract:
Contrast enhancement by Gadolinium-based contrast agents (GBCAs) is a vital tool for tumor diagnosis in neuroradiology. Based on brain MRI scans of glioblastoma before and after Gadolinium administration, we address enhancement prediction by neural networks with two new contributions.
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Brief introduction of the dida co-author(s) and relevance for dida's ML developments.
Fabian Altekrüger
During his mathematics studies at TU Berlin, Fabian focused on functional analysis. In his subsequent doctoral research, he worked on the regularization and solution of Bayesian inverse problems in mathematical image processing, combining mathematical methods with neural networks. In this context, Fabian developed and applied conditional generative models, always with an emphasis on the stability and robustness of the methods. At dida, he contributes his skills as a machine learning scientist.