Frederik Lange
Post-doctoral Research Assistant
Research Summary
My research focuses on developing and implementing algorithms for automated medical imaging analysis.
Currently I am developing a multi-model, non-linear registration tool which leverages the data from each modality to inform the transformation between subject space and reference space. The overall aim of this tool is to provide a single, unified framework for bringing multi-modal datasets into a common space.
Additionally, I am working towards addressing and overcoming computational bottlenecks in image analysis through leveraging the massively parallel architecture of general purpose graphics processing units (GPGPUs). The goal of this work is to reduce the runtime of commonly used analysis tools, particularly for use in the pre-processing pipelines of large imaging studies.
Recent publications
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Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge
Journal article
Raman B. et al, (2021), EClinicalMedicine, 31, 100683 - 100683
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A Symmetric Prior for the Regularisation of Elastic Deformations: Improved Anatomical Plausibility in Nonlinear Image Registration
Journal article
LANGE F. et al, (2020), NeuroImage
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Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque
Conference paper
Lange F. et al, (2020)