CSVR: Combined Surface and Volume Registration for Neonatal Brain MRI

Saga N.B. Masui, Yourong Guo, Mohamed A. Suliman, Mattias P Heinrich, Nashira Baena, Irina Grigorescu, Logan Zane John Williams, Ashleigh Davies, Vanessa Kyriakopoulou, Gráinne McAlonan, Jonathan O'Muircheartaigh, Emma C. Robinson

Keywords: Image registration, Combined surface-volume registration, Neuroimaging, Surface-modelling, Deep learning, Discrete optimisation, Hierarchical registration

TL;DR: We introduce CSVR, a learning-based combined surface-volume registration framework for neonatal brain MRI, leveraging recent developments in hierarchical registration and discrete optimisation.

Abstract: Nonlinear image registration is a cornerstone of neuroimaging analysis, supporting both qualitative and quantitative comparisons of brain structures across individuals and over time. While traditional volumetric registration methods, driven by voxel intensities, achieve good alignment of subcortical regions, they generally fail to capture correspondences between highly convoluted and variable cortical shapes. Surface-based methods, which instead regularise mappings as geodesics along the cortical sheet, yield improved cortical alignment but ignore the subcortical domain, limiting their utility for whole-brain analyses. A unified registration framework would address these limitations to enable integrated analysis of cortical and subcortical structures and the neuronal fibres that connect them. However, achieving this is challenging, since matching heterogeneous cortical shapes implies large volumetric displacements local to the cortex. To overcome these challenges, we introduce CSVR, the first deep learning-based framework for combined surface–volume registration of neonatal MRI. By integrating hierarchical registration strategies with discrete optimisation, CSVR achieves accurate, smooth, and anatomically plausible alignment of the entire brain.

Primary Subject Area: Image Registration

Secondary Subject Area: Application: Neuroimaging

Registration Requirement: Yes

Reproducibility: https://github.com/minisagan/CSVR

Visa & Travel: No

Read CFP & Author Instructions: Yes

Originality Policy: Yes

Single-blind & Not Under Review Elsewhere: Yes

LLM Policy: Yes

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Submission Number: 318