7 papers
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…
Geometry-Aware Uncertainty Coresets for Robust Visual In-Context Learning in Histopathology
Franciskus Xaverius Erick, Johanna Paula Müller, Bernhard Kainz
Vision-language models (VLMs) can couple visual perception with open-ended clinical reasoning, making them attractive for computational histopathology. However, fine-tuning billion…
Wasserstein Equilibrium Decoding for Reliable Medical Visual Question Answering
Luca Hagen, Johanna P. Müller, Weitong Zhang +2
Small vision-language models (2-8B) are well-suited for clinical deployment due to privacy constraints, limited connectivity, and low-latency requirements favouring on-device or on…
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…
Label-free Motion-Conditioned Diffusion Model for Cardiac Ultrasound Synthesis
Zhe Li, Hadrien Reynaud, Johanna P Müller +1
Ultrasound echocardiography is essential for the non-invasive, real-time assessment of cardiac function, but the scarcity of labelled data, driven by privacy restrictions and the c…
Diffusing the Blind Spot: Uterine MRI Synthesis with Diffusion Models
Johanna P. Müller, Anika Knupfer, Pedro Blöss +3
Despite significant progress in generative modelling, existing diffusion models often struggle to produce anatomically precise female pelvic images, limiting their application in g…