Ultrasound Simulation

Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation
A two-stage framework generates abdominal ultrasound images from semantic labels using physics-based supervision and anatomy-preserving refinement, enabling controlled simulations of motion, deformations, and pathological findings without patient-specific CT volumes at inference time.
Santiago Vitale, Duilio Deangeli, Ignacio Larrabide, José Ignacio Orlando
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Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation
Improving realism in abdominal ultrasound simulation combining a segmentation-guided loss and polar coordinates training
We propose a GAN that improves the realism of US simulations by combining a segmentation-guided loss function with polar coordinates training, leading to more realistic organ boundaries and reduced artifacts.
Santiago Vitale, Alejandro Díaz, José Ignacio Orlando, Emmanuel Iarussi, Ignacio Larrabide
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Improving realism in abdominal ultrasound simulation combining a segmentation-guided loss and polar coordinates training
Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs
We applied CycleGANs to improve realism in ultrasound simulation based on ray-casting methods.
Santiago Vitale, José Ignacio Orlando, Emmanuel Iarussi, Ignacio Larrabide
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