12 papers
Implicit representations are dead. Long live explicit primitives!
Nil Stolt-Ansó, Maik Dannecker, Wenqi Huang +2
Continuous parameterization of medical data has emerged as a powerful paradigm for resolution-independent image representation. While Implicit Neural Representations offer high fid…
NISF++: Geometrically-grounded implicit representations of 3D+time cardiac function from 2D short- and long-axis MR views
Nil Stolt-Ansó, Maik Dannecker, Steven Jia +2
Clinical acquisition in cardiac magnetic resonance (CMR) imaging involves obtaining cross-sectional planes of the heart along the radial and longitudinal directions. Despite these…
PRIME-SVR: Physics-infoRmed Implicit Multi-Echo Slice-to-Volume Reconstruction for Fetal T2 mapping
Busra Bulut, Maik Dannecker, Thomas Sanchez +14
Slice-to-volume reconstruction (SVR) is the standard method for obtaining high-resolution (HR) 3D fetal brain volumes from motion-corrupted 2D MRI slice stacks acquired in multiple…
Fast and Explicit: Slice-to-Volume Reconstruction via 3D Gaussian Primitives with Analytic Point Spread Function Modeling
Maik Dannecker, Steven Jia, Nil Stolt-Ansó +4
Recovering high-fidelity 3D images from sparse or degraded 2D images is a fundamental challenge in medical imaging, with broad applications ranging from 3D ultrasound reconstructio…
Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe +1
Fine-tuning large language models (LLMs) with limited data poses a practical challenge in low-resource languages, specialized domains, and constrained deployment settings. While pr…
Evaluation of Deformable Image Registration under Alignment-Regularity Trade-off
Vasiliki Sideri-Lampretsa, Daniel Rueckert, Huaqi Qiu
Evaluating deformable image registration (DIR) is challenging due to the inherent trade-off between achieving high alignment accuracy and maintaining deformation regularity. Howeve…