44 citations · 44 across the 3 of their papers we have counts for
6 papers
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…
General Vision Encoder Features as Guidance in Medical Image Registration
Fryderyk Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa +5
General vision encoders like DINOv2 and SAM have recently transformed computer vision. Even though they are trained on natural images, such encoder models have excelled in medical…
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…
MAD: Modality Agnostic Distance Measure for Image Registration
Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu +2
Multi-modal image registration is a crucial pre-processing step in many medical applications. However, it is a challenging task due to the complex intensity relationships between d…
Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
Robert Graf, Joachim Schmitt, Sarah Schlaeger +8
Background: Automated segmentation of spinal MR images plays a vital role both scientifically and clinically. However, accurately delineating posterior spine structures presents ch…
Investigating Pulse-Echo Sound Speed Estimation in Breast Ultrasound with Deep Learning
Walter A. Simson, Magdalini Paschali, Vasiliki Sideri-Lampretsa +2
Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians with diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound spe…