Automatic skull-template alignment without a guidance image

TL;DR

This paper introduces MOFI, a novel method for aligning skull templates in transcranial ultrasound without relying on MRI guidance, by minimizing differences between simulated and observed acoustic data.

Contribution

The paper presents MOFI, a new approach that enables skull-template registration solely based on acoustic data, eliminating the need for guidance images like MRI.

Findings

Accurately recovers skull template positions in silico

Successfully aligns skull templates in vitro

Potential to replace MRI-guided registration in clinical settings

Abstract

Transcranial ultrasound must overcome the significant challenge of the human skull, limiting both imaging and therapeutic applications. While high-fidelity numerical simulations can compensate for skull-induced distortions, they require precise skull templates (typically derived from Computed Tomography, CT) and spatial alignment to the patient's anatomy. Current alignment relies on concurrent Magnetic Resonance Imaging (MRI) for registration, introducing financial, logistical, and throughput barriers. To overcome these challenges, we present Manifold Optimisation for Full-Waveform Inversion (MOFI), a method to register skull templates without using a guidance image. Our method aligns the skull template by minimising the difference between simulated and observed radio-frequency acoustic data. We demonstrate that MOFI accurately recovers the position of skull templates in silico and in vitro, offering an alternative to MRI guidance-based registration. These results indicate that MOFI has the potential to be a practical alternative to MRI-guided approaches, reducing the barriers to wider clinical adoption of transcranial ultrasound.