Transcranial ultrasound simulation with uncertainty estimation
Antonio Stanziola, Jos\'e A. Pineda-Pardo, Bradley Treeby

TL;DR
This paper presents a computationally efficient method to estimate uncertainty in transcranial ultrasound simulations caused by variability in skull and brain tissue properties, validated against Monte Carlo simulations.
Contribution
It introduces a linear uncertainty propagation approach for predicting acoustic field uncertainty in transcranial ultrasound simulations, improving efficiency over traditional methods.
Findings
Uncertainty estimates closely match Monte Carlo results.
Method reduces computational cost significantly.
Applicable to focused bowl transducers at 500 kHz.
Abstract
Transcranial ultrasound simulations are increasingly used to predict in situ exposure parameters for ultrasound therapies in the brain. However, there can be considerable uncertainty in estimating the acoustic medium properties of the skull and brain from computed tomography (CT) images. Here, we show how the resulting uncertainty in the simulated acoustic field can be predicted in a computationally efficient way using linear uncertainty propagation. Results for a representative transcranial simulation using a focused bowl transducer at 500 kHz show good agreement with unbiased uncertainty estimates obtained using Monte Carlo.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsUltrasound Imaging and Elastography · Ultrasound and Hyperthermia Applications · Advanced MRI Techniques and Applications
