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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
Panda: Unsupervised Pelvic Anomaly Detection for Real-Time MR Imaging
Anika Knupfer, Maximilian Lindholz, Johanna Paula Müller +4
Female pelvic diseases remain an under researched area characterized by often delayed diagnosis. While pelvic MRI offers superior soft-tissue contrast for diagnosis and image-guide…
cs.CV2026
Unsupervised Anomaly Detection of Diseases in the Female Pelvis for Real-Time MR Imaging
Anika Knupfer, Johanna P. Müller, Jordina A. Verdera +9
Pelvic diseases in women of reproductive age represent a major global health burden, with diagnosis frequently delayed due to high anatomical variability, complicating MRI interpre…