4 papers
Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation
Santiago Vitale, Duilio Deangeli, Ignacio Larrabide +1
Purpose: Current abdominal ultrasound (US) simulation methods often require CT-based anatomical references for ray-casting, limiting deformation and pathology variability. We propo…
Pseudo-Label Foreground Quality Weighting for Domain-Generalized Fundus Image Segmentation
Lucas Gabriel Telesco, José Ignacio Orlando
Optic disc (OD) and optic cup (OC) segmentation is central to automated glaucoma assessment, but models trained on limited labeled fundus datasets often degrade under domain shift.…
Can Coding Agents Build Robust Baselines? A Skill-Based Approach for Automating the Medical Imaging Model-Development Pipeline
Eugenia Moris, José Ignacio Orlando
Developing competitive deep learning baselines for medical imaging remains a highly iterative process requiring literature review, implementation, experimentation, and expert refin…
Semi-Supervised Multi-Task Learning for Interpretable Quality As- sessment of Fundus Images
Lucas Gabriel Telesco, Danila Nejamkin, Estefanía Mata +8
Retinal image quality assessment (RIQA) supports computer-aided diagnosis of eye diseases. However, most tools classify only overall image quality, without indicating acquisition d…