MeshDeform: Surface Reconstruction of Subcortical Structures in Human Brain MRI

Inf Process Med Imaging. 2023 Jun;13939:536-547. doi: 10.1007/978-3-031-34048-2_41. Epub 2023 Jun 8.ABSTRACTSurface reconstruction of cortical and subcortical structures is crucial for brain morphological studies. Existing deep learning surface reconstruction methods, such as DeepCSR and Vox2Surf, learn an implicit field function for computing the isosurface, but do not consider mesh topology. In this paper, we propose a novel and efficient deep learning mesh deformation network, called MeshDeform, to reconstruct topologically correct surfaces of subcortical structures using brain MR images. MeshDeform combines features extracted from a U-Net encoder with mesh deformation blocks to predict surfaces of subcortical structures by deforming spherical mesh templates. MeshDeform is able to reconstruct in less than 10 seconds the surfaces of a left-right pair of subcortical structures with subvoxel accuracy. Reconstruction of all 17 subcortical structures takes less than one and a half minutes. By contrast, Vox2Surf takes about 20-30 minutes for all subcortical structures. Visual and quantitative evaluation on the Human Connectome Project (HCP) dataset demonstrate that MeshDeform generates accurate subcortical surfaces in limited time while preserving mesh topology.PMID:37915753 | PMC:PMC10617631 | DOI:10.1007/978-3-031-34048-2_41

Source: Inf Process Med Imaging - November 2, 2023 Category: Radiology Authors: Junjie Zhao Siyuan Liu Sahar Ahmad Yap Pew-Thian Source Type: research