5 papers · 1 filter
Implicit Neural Representations for Multimodal Longitudinal Image Imputation and Interpolation
Sina Wendrich, Lukas Förner, Zoe Reinke +5
Longitudinal multiparametric MRI is central to follow-up imaging in oncology, yet real-world clinical data are characterised by missing sequences, heterogeneous acquisition protoco…
Inverse Bayesian Inference for Extracting Lesion Dynamics from Longitudinal Spectral CT
Lukas Förner, Melina Wördehoff, Julian Steffens +6
Longitudinal medical imaging captures temporal evolution of lesions, yet extracting the underlying dynamical parameters governing this evolution remains challenging. We propose an…
Performance and Explainability Requirements of Evolutionary Algorithms in Real-World Physics-Informed Optimization
Helena Stegherr, Michael Heider, Nils Meyer +7
Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simplified problems and optimizati…
Bridging MRI and PET physiology: Untangling complementarity through orthogonal representations
Sonja Adomeit, Kartikay Tehlan, Lukas Förner +7
Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modality-specific. Clarifying this di…
Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis
Kartikay Tehlan, Lukas Förner, Sina Wendrich +5
We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-specific energy modelling in sequence space. Rather than operating on images with s…