ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation.
Neuroimage 2020;
220:117107. [PMID:
32622984 PMCID:
PMC7903162 DOI:
10.1016/j.neuroimage.2020.117107]
[Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 06/17/2020] [Accepted: 06/25/2020] [Indexed: 11/27/2022] Open
Abstract
This paper presents Contextual Fibre Growth (ConFiG), an approach to generate white matter numerical phantoms by mimicking natural fibre genesis. ConFiG grows fibres one-by-one, following simple rules motivated by real axonal guidance mechanisms. These simple rules enable ConFiG to generate phantoms with tuneable microstructural features by growing fibres while attempting to meet morphological targets such as user-specified density and orientation distribution. We compare ConFiG to the state-of-the-art approach based on packing fibres together by generating phantoms in a range of fibre configurations including crossing fibre bundles and orientation dispersion. Results demonstrate that ConFiG produces phantoms with up to 20% higher densities than the state-of-the-art, particularly in complex configurations with crossing fibres. We additionally show that the microstructural morphology of ConFiG phantoms is comparable to real tissue, producing diameter and orientation distributions close to electron microscopy estimates from real tissue as well as capturing complex fibre cross sections. Signals simulated from ConFiG phantoms match real diffusion MRI data well, showing that ConFiG phantoms can be used to generate realistic diffusion MRI data. This demonstrates the feasibility of ConFiG to generate realistic synthetic diffusion MRI data for developing and validating microstructure modelling approaches.
We present ConFiG, a biologically motivated numerical phantom generator for white matter.
ConFiG produces phantoms with state-of-the-art density and realistic microstructure.
Diffusion MRI simulations in ConFiG phantoms are comparable to real dMRI signals.
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