PISCO: Self-Supervised k-Space Regularization for Improved Neural Implicit k-Space Representations of Dynamic MRI

arXiv:2501.09403 · eess.IV, cs.CV, cs.LG, eess.SP, physics.med-ph · Submitted 2025-01-16 · Read on arXiv

Veronika Spieker, Hannah Eichhorn, Wenqi Huang, Jonathan K. Stelter, Tabita Catalan, Rickmer F. Braren, Daniel Rueckert, Francisco Sahli Costabal, Kerstin Hammernik, Dimitrios C. Karampinos, Claudia Prieto, Julia A. Schnabel

eess.IV, cs.CV, cs.LG, eess.SP, physics.med-ph

Submitted: 2025-01-16

Updated: 2026-08-19

Code: https://github.com/compai-lab/2025-pisco-spieker

Terminology

Consistency — 33× in this paper · explained in 3 episodes
Regularization — 19× in this paper · explained in 3 episodes
Loss Function — 9× in this paper · explained in 2 episodes
Self-consistency — 9× in this paper · explained in 2 episodes
Calibration — 7× in this paper · explained in 7 episodes
Redundancy — 3× in this paper · explained in 2 episodes
Adam — 2× in this paper · explained in 2 episodes
Representation Learning — 2× in this paper · explained in 2 episodes
Robustness — 2× in this paper · explained in 5 episodes
Ablation — 1× in this paper · explained in 1 episode
Activation Function — 1× in this paper · explained in 1 episode
Adaptation — 1× in this paper · explained in 1 episode
Computational overhead — 1× in this paper · explained in 2 episodes
Downstream Tasks — 1× in this paper · explained in 2 episodes
Generative Model — 1× in this paper · explained in 2 episodes
Generative Models — 1× in this paper · explained in 2 episodes
Hysteresis — 1× in this paper · explained in 3 episodes
Inverse Problem — 1× in this paper · explained in 2 episodes
Objective Function — 1× in this paper · explained in 2 episodes
Self-Supervised Learning — 1× in this paper · explained in 7 episodes

Terminology

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