collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

Segmentation Pre-training for Label-Efficient Lumbar Spine Degeneration Grading

Monzon Maria, Zisserman Andrew, Jutzeler Catherine R. +1

Automated assessment of degenerative pathology in the lumbar spine on magnetic resonance imaging (MRI) requires access to large-scale datasets of expert-annotated radiological grad…

cs.CV2026

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…

cs.CV2025

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…