Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation
Purpose: Current abdominal ultrasound (US) simulation methods often require CT-based anatomical references for ray-casting, limiting deformation and pathology variability. We propose a learning-based pipeline trained to predict physics-based images derived from CT scans from semantic labels, enabling controlled simulations without patient-specific CT volumes at inference time. Methods: We introduce a two-stage pipeline that maps anatomical segmentations to realistic US images through a simplified US image. Stage~I synthesizes this image from semantic labels using models trained on CT-based ray-casting outputs. Stage~II refines it into a realistic US scan using anatomically guided unpaired...
| Authors | Santiago Vitale, Duilio Deangeli, Ignacio Larrabide et al. |
|---|---|
| Primary category | eess.IV |
| Published | 2 October 2026 |
| Last updated at source | 2 October 2026 |
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