T1 magnetic resonance imaging head segmentation for diffuse optical tomography and electroencephalography

Abstract

Abstract. Accurate segmentation of structural magnetic resonance images is critical for creating subject-specific forward models for functional neuroimaging source localization. In this work, we present an innovative segmentation algorithm that generates accurate head tissue layer thicknesses that are needed for diffuse optical tomography (DOT) data analysis. The presented algorithm is compared against other publicly available head segmentation methods. The proposed algorithm has a root mean square scalp thickness error of 1.60 mm, skull thickness error of 1.96 mm, and summed scalp and skull error of 1.49 mm. We also introduce a segmentation evaluation metric that evaluates the accuracy of tissue layer thicknesses in regions of the head where optodes are typically placed. The presented segmentation algorithm and evaluation metric are tools for improving the localization accuracy of neuroimaging with DOT, and also multimodal neuroimaging such as combined electroencephalography and DOT.

How short is short? Optimum source–detector distance for short-separation channels in functional near-infrared spectroscopy

“…The nonlinear MNI-ICBM152 atlas 25 was the basis of our adult head model. A multilayer tissue mask, segmented into five layers [skull, scalp, CSF, gray matter (GM), and white matter (WM)], was obtained using the MRI tissue probability maps for brain tissue segmentation and the methods developed by Perdue and Diamond 26 for scalp and skull segmentation. Surface meshes for scalp, skull, CSF, and GM were created with the iso2mesh toolbox 27 with the cgalmesher option.…”

Data-driven approach to optimum wavelength selection for diffuse optical imaging

“…24 The scalp and skull layers were extracted from the average T1 MRI images using the methodology proposed by Perdue et al 25 Combined with the segmentations present in the ICBM atlas, this yielded a 5-part tissue mask (scalp, skull, cerebrospinal fluid, gray matter, and white matter) with a voxel size of 1 mm × 1 mm × 1 mm. The Iso2Mesh package 26,27 was then applied to produce a 5 layer tetrahedral volume mesh and a cortical surface mesh from the tissue mask.…”

The Effect of a Transcranial Channel as a Skull/Brain Interface in High-Definition Transcranial Direct Current Stimulation—A Computational Study

“…The model was segmented by the white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), skull, and scalp, respectively. Dura mater was made artificially by deleting 0.5 mm53 of the boundary between the CSF and skull layer based on the assumption that it was mapped to the skull layer4254. Then, we constructed disc-type electrodes (height = 1 mm; radius = 4 mm) to form a 4 × 1 HD-tDCS electrode montage with the “active” center electrode on the target hand knob in the precentral gyrus55, and with four “return” electrodes positioned in a circular fashion8.…”