2 citations · 2 across the 13 of their papers we have counts for
5 papers · 1 filter
Self-Supervised Radiograph Anatomical Region Classification -- How Clean Is Your Real-World Data?
Simon Langer, Jessica Ritter, Rickmer Braren +2
Modern deep learning-based clinical imaging workflows rely on accurate labels of the examined anatomical region. Knowing the anatomical region is required to select applicable down…
From Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review
Anna Reithmeir, Veronika Spieker, Vasiliki Sideri-Lampretsa +3
Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration i…
Interpretable deformable image registration: A geometric deep learning perspective
Vasiliki Sideri-Lampretsa, Nil Stolt-Ansó, Huaqi Qiu +4
Deformable image registration poses a challenging problem where, unlike most deep learning tasks, a complex relationship between multiple coordinate systems has to be considered. A…
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…
Intensity-based 3D motion correction for cardiac MR images
Nil Stolt-Ansó, Vasiliki Sideri-Lampretsa, Maik Dannecker +1
Cardiac magnetic resonance (CMR) image acquisition requires subjects to hold their breath while 2D cine images are acquired. This process assumes that the heart remains in the same…