4 citations · 8 across the 9 of their papers we have counts for
9 papers
Beyond Fluency: A Clinical Benchmark and Anomaly-Enhanced Baseline for Spine MRI Report Generation
Bruno Palau, Franziska Vogt, Daria Laslo +4
Radiology reporting is time-consuming and subject to inter-rater variability, making automated report generation an attractive clinical application for Vision-Language Models (VLMs…
Enhancing Low Back Pain Assessment with Diffusion Models for Lumbar Spine MRI Segmentation
Maria Monzon, Thomas Iff, Ender Konukoglu +1
This study introduces a diffusion-based framework for robust and accurate semantic segmentation of lumbar spine MRI scans from patients with low back pain (LBP), regardless of whet…
Be Indiscrete: The Benefits of Learning Continuous Spine Degeneration Severity Scores
Maria Monzon, Andrew Zisserman, Robin Y. Park +2
Lumbar spine degeneration is a major contributor to chronic low back pain and is routinely assessed on MRI using ordinal grading systems, e.g. normal, mild, moderate, severe. Conse…
Mechanistic Learning with Guided Diffusion Models to Predict Spatio-Temporal Brain Tumor Growth
Daria Laslo, Efthymios Georgiou, Marius George Linguraru +4
Predicting the spatio-temporal progression of brain tumors is essential for guiding clinical decisions in neuro-oncology. We propose a hybrid mechanistic learning framework that co…
Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients
Maria Monzon, Thomas Iff, Ender Konukoglu +1
This study introduces a diffusion-based framework for robust and accurate segmenton of vertebrae, intervertebral discs (IVDs), and spinal canal from Magnetic Resonance Imaging~(MRI…
A review of mechanistic learning in mathematical oncology
John Metzcar, Catherine R. Jutzeler, Paul Macklin +2
Mechanistic learning, the synergistic combination of knowledge-driven and data-driven modeling, is an emerging field. In particular, in mathematical oncology, the application of ma…
Genetic prediction of quantitative traits: a machine learner's guide focused on height
Lucie Bourguignon, Caroline Weis, Catherine R. Jutzeler +1
Machine learning and deep learning have been celebrating many successes in the application to biological problems, especially in the domain of protein folding. Another equally comp…
Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification
Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck +1
Owing to its pristine soft-tissue contrast and high resolution, structural magnetic resonance imaging (MRI) is widely applied in neurology, making it a valuable data source for ima…
Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design
Sarah C. Brüningk, Felix Hensel, Catherine R. Jutzeler +1
Alzheimer's disease (AD) is associated with local (e.g. brain tissue atrophy) and global brain changes (loss of cerebral connectivity), which can be detected by high-resolution str…