3 papers
cs.CV2026
STORK: Spatio-Temporal Observation of uterine contRactions via neural networKs
Melissa Schween, Tristan Gottwald, Jordina Aviles Verdera +3
Uterine contractions in fetal MRI are typically identified manually and discarded, limiting insights into contraction dynamics. We formalize Uterine Contractile Activity Detection…
cs.CV2026
FlowMoDL: Model-Based Deep Learning with Conjugate-Gradient Data Consistency for Highly Accelerated 4D Flow MRI Reconstruction
Tristan Gottwald, Michelle Bruch, Mubashir-Ul Hassan +6
We present FlowMoDL, an unrolled neural network for highly accelerated 4D flow MRI reconstruction that directly optimizes for both anatomical magnitude and phase-derived velocity a…
cs.CV2026
FLEET: Token-Based Feature Extraction for Event Camera-based Reinforcement Learning
Tristan Gottwald, Maximilian Schier, Melanie Schaller +1
Event cameras generate asynchronous, high-frequency data streams offering spatially sparse information at lower latency than traditional cameras. In principle, these properties sho…