6 citations · 7 across the 5 of their papers we have counts for
5 papers
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…
Global and Local Contrastive Learning for Joint Representations from Cardiac MRI and ECG
Alexander Selivanov, Philip Müller, Özgün Turgut +2
An electrocardiogram (ECG) is a widely used, cost-effective tool for detecting electrical abnormalities in the heart. However, it cannot directly measure functional parameters, suc…
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…
Investigation on the generalization of the Sampled Policy Gradient algorithm
Nil Stolt Ansó
The Sampled Policy Gradient (SPG) algorithm is a new offline actor-critic variant that samples in the action space to approximate the policy gradient. It does so by using the criti…
Sampled Policy Gradient for Learning to Play the Game Agar.io
Anton Orell Wiehe, Nil Stolt Ansó, Madalina M. Drugan +1
In this paper, a new offline actor-critic learning algorithm is introduced: Sampled Policy Gradient (SPG). SPG samples in the action space to calculate an approximated policy gradi…