5 papers · 1 filter
Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…
Beyond the LUMIR challenge: The pathway to foundational registration models
Junyu Chen, Shuwen Wei, Joel Honkamaa +33
Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundati…
Physiological neural representation for personalised tracer kinetic parameter estimation from dynamic PET
Kartikay Tehlan, Thomas Wendler
Dynamic positron emission tomography (PET) with [F]FDG enables non-invasive quantification of glucose metabolism through kinetic analysis, often modelled by the two-tissue c…
Anatomy-constrained modelling of image-derived input functions in dynamic PET using multi-organ segmentation
Valentin Langer, Kartikay Tehlan, Thomas Wendler
Accurate kinetic analysis of [F]FDG distribution in dynamic positron emission tomography (PET) requires anatomically constrained modelling of image-derived input functions (…
Fine-Tuning TransMorph with Gradient Correlation for Anatomical Alignment
Lukas Förner, Kartikay Tehlan, Thomas Wendler
Unsupervised deep learning is a promising method in brain MRI registration to reduce the reliance on anatomical labels, while still achieving anatomically accurate transformations.…