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Surface-driven registration method for the structure-informed segmentation of diffusion MR images

View ORCID ProfileOscar Esteban, View ORCID ProfileDominique Zosso, View ORCID ProfileAlessandro Daducci, Meritxell Bach-Cuadra, View ORCID ProfileMaría J. Ledesma-Carbayo, View ORCID ProfileJean-Philippe Thiran, View ORCID ProfileAndres Santos
doi: https://doi.org/10.1101/018945
Oscar Esteban
aBiomedical Image Technologies (BIT), ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
bCentro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
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  • For correspondence: phd@oscaresteban.es
Dominique Zosso
cDepartment of Mathematics, University of California, Los Angeles (UCLA), Los Angeles, CA, US
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Alessandro Daducci
dSignal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Meritxell Bach-Cuadra
eDept. of Radiology, CIBM, University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
dSignal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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María J. Ledesma-Carbayo
aBiomedical Image Technologies (BIT), ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
bCentro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
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Jean-Philippe Thiran
dSignal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
eDept. of Radiology, CIBM, University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Andres Santos
aBiomedical Image Technologies (BIT), ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
bCentro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
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Abstract

Current methods for processing diffusion MRI (dMRI) to map the connectivity of the human brain require precise delineations of anatomical structures. This requirement has been approached by either segmenting the data in native dMRI space or mapping the structural information from T1-weighted (T1w) images. The characteristic features of diffusion data in terms of signal-to-noise ratio, resolution, as well as the geometrical distortions caused by the inhomogeneity of magnetic susceptibility across tissues hinder both solutions. Unifying the two approaches, we propose regseg, a surface-to-volume nonlinear registration method that segments homogeneous regions within multivariate images by mapping a set of nested reference-surfaces. Accurate surfaces are extracted from a T1w image of the subject, using as target image the bivariate volume comprehending the fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) maps derived from the dMRI dataset. We first verify the accuracy of regseg on a general context using digital phantoms distorted with synthetic and random deformations. Then we establish an evaluation framework using undistorted dMRI data from the Human Connectome Project (HCP) and realistic deformations derived from the inhomogeneity fieldmap corresponding to each subject. We analyze the performance of regseg computing the misregistration error of the surfaces estimated after being mapped with regseg onto 16 datasets from the HCP. The distribution of errors shows a 95% CI of 0.56–0.66 mm, that is below the dMRI resolution (1.25 mm, isotropic). Finally, we cross-compare the proposed tool against a nonlinear b0-to-T2w registration method, thereby obtaining a significantly lower misregistration error with regseg. The accurate mapping of structural information in dMRI space is fundamental to increase the reliability of network building in connectivity analyses, and to improve the performance of the emerging structure-informed techniques for dMRI data processing.

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Posted February 03, 2016.
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Surface-driven registration method for the structure-informed segmentation of diffusion MR images
Oscar Esteban, Dominique Zosso, Alessandro Daducci, Meritxell Bach-Cuadra, María J. Ledesma-Carbayo, Jean-Philippe Thiran, Andres Santos
bioRxiv 018945; doi: https://doi.org/10.1101/018945
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Surface-driven registration method for the structure-informed segmentation of diffusion MR images
Oscar Esteban, Dominique Zosso, Alessandro Daducci, Meritxell Bach-Cuadra, María J. Ledesma-Carbayo, Jean-Philippe Thiran, Andres Santos
bioRxiv 018945; doi: https://doi.org/10.1101/018945

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