271 citations · 603 across the 47 of their papers we have counts for
22 papers · 1 filter
Bias in Unsupervised Anomaly Detection in Brain MRI
Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler +3
Unsupervised anomaly detection methods offer a promising and flexible alternative to supervised approaches, holding the potential to revolutionize medical scan analysis and enhance…
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space
Veronika Spieker, Wenqi Huang, Hannah Eichhorn +7
Motion-resolved reconstruction for abdominal magnetic resonance imaging (MRI) remains a challenge due to the trade-off between residual motion blurring caused by discretized motion…
Sparse annotation strategies for segmentation of short axis cardiac MRI
Josh Stein, Maxime Di Folco, Julia Schnabel
Short axis cardiac MRI segmentation is a well-researched topic, with excellent results achieved by state-of-the-art models in a supervised setting. However, annotating MRI volumes…
Attribute Regularized Soft Introspective VAE: Towards Cardiac Attribute Regularization Through MRI Domains
Maxime Di Folco, Cosmin Bercea, Julia A. Schnabel
Deep generative models have emerged as influential instruments for data generation and manipulation. Enhancing the controllability of these models by selectively modifying data att…
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik +4
Motion represents one of the major challenges in magnetic resonance imaging (MRI). Since the MR signal is acquired in frequency space, any motion of the imaged object leads to comp…
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection
Cosmin I Bercea, Benedikt Wiestler, Daniel Rueckert +1
Early and accurate disease detection is crucial for patient management and successful treatment outcomes. However, the automatic identification of anomalies in medical images can b…