Published April 8, 2019
| Version v1
Conference paper
Analytical Fiber ODF Reconstruction in 3D Polarized Light Imaging: Performance Assessment
Contributors
Others:
- Computational Imaging of the Central Nervous System (ATHENA) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Institute of Neuroscience and Medicine [Jülich] (INM-1)
- This work was partly supported by ANR "MOSIFAH" under ANR-13-MONU-0009-01, the ERC under the European Union's Horizon 2020 research and innovation program (ERC Advanced Grant agreement No694665:CoBCoM).?This work has also received partially funding from theEuropean Union's Horizon 2020 Research and Innovation Program underGrant Agreement No. 7202070 (Human Brain Project SGA2).?The au-thors gratefully acknowledge the computing time granted by the JARA-HPC Vergabegremium and provided on the JARA-HPC Partition part of the super-computer JURECA at Forschungszentrum Jülich
- ANR-13-MONU-0009,MOSIFAH,Modélisation et simulation multimodales et multiéchelles de l'architecture des fibres myocardiques du cœur humain(2013)
- European Project: 694665,H2020 ERC,ERC-2015-AdG,CoBCoM(2016)
Description
Three dimensional Polarized Light Imaging (3D-PLI) allows to map the spatial fiber structure of postmortem tissue at a sub-millimeter resolution, thanks to its birefringence property. Different methods have been recently proposed to reconstruct the fiber orientation distribution function (fODF) from high-resolution vector data provided by 3D-PLI. Here, we focus on the analytical fODF computation approach, which uses the spherical harmonics to represent the fODF and analytically computes the spherical harmonics coefficients via the spherical Fourier transform. This work deals with the assessment of the performance of this approach on rich synthetic data which simulates the geometry of the neuronal fibers and on human brain dataset. A computational complexity and robustness to noise analysis demonstrate the interest and great potential of the approach.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://hal.inria.fr/hal-01988262
- URN
- urn:oai:HAL:hal-01988262v1
Origin repository
- Origin repository
- UNICA