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Oliver Josephs

Publications and source records attributed to Oliver Josephs.

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MORSE-PI -- Flexible and artefact-free image reconstruction for structural and functional QSM and other phase-critical imaging applications

Phase imaging applications such as QSM are highly sensitive to noise amplifications, phase singularities, and other artefacts, particularly in challenging scenarios such as ultra-high field (7T), under-sampled or single-echo acquisitions. We present a novel image reconstruction method, MORSE-PI, designed to produce high-SNR, artefact-free, and singularity-free phase images for both structural and functional phase-based brain imaging. MORSE-PI extends our previous approach, MORSE, by introducing a Virtual Reference Coil (VRC). The VRC is constructed as a linear combination of coil sensitivity maps, with correlations enhanced between coil elements using the noise covariance matrix. Such a VRC ensures robust signal support across the entire brain and is used to correct phase offsets in the MORSE-derived coil sensitivity estimates, resulting in artefact-free, high SNR phase. Compared to GRAPPA with ASPIRE phase correction, MORSE-PI demonstrates greater robustness to artefacts such as noise amplification and aliasing, and shows improved reproducibility in structural imaging at both 3T and 7T. Unlike ESPIRiT and GRAPPA combined with adaptive coil combination methods, MORSE-PI yields singularity-free phase maps. MORSE-PI enables high-SNR reconstructions even for the most challenging scenarios, such as single-echo EPI at 7T. Its efficient, containerised implementation using the Gadgetron framework supports deployment on the MRI scanner console during measurements. MORSE-PI offers a flexible and computationally efficient solution for generating high-SNR, artefact- and singularity-free phase images in both single- and multi-echo GRE and EPI acquisitions. This makes it particularly well-suited for structural and functional QSM, as well as other phase-based MRI applications. Its robustness and rapid computational time facilitate efficient deployment on scanners across field strengths.

physics.med-ph

MORSE: Multiple Orthogonal Reference Sensitivity Encoding

Parallel imaging is ubiquitous in MRI, enabling diverse applications such as ultra-high-resolution functional and quantitative imaging with greater temporal resolution or reduced scan times respectively. Successful unfolding is contingent on robust and accurate estimation of the relative coil sensitivities, which often involves computation times that preclude real-time deployment. Here we present a computationally-efficient method of robustly estimating coil sensitivities, and reconstructing under-sampled images using a data-driven regularised SENSE formalism. Our MORSE scheme estimates multiple sensitivities per voxel to address issues such as rapidly varying sensitivities, chemical shift artefact, or insufficient fields of view and provides a data-driven regularisation term for noise control. Exemplar structural and functional image reconstructions at 3T and 7T are presented and compared with a vendor-provided GRAPPA reconstruction as well as state-of-the-art ESPIRiT and LORAKS algorithms. MORSE consistently produced high-quality, artefact-free images with reconstruction times feasible for real-time deployment. It is flexible and robust, and made available to the community in open-source as a library of functions within the vendor-agnostic Gadgetron image reconstruction framework.

physics.med-ph