UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Contextual fibre growth to generate realistic axonal packing for diffusion MRI simulation

Callaghan, R; Alexander, DC; Zhang, H; Palombo, M; (2019) Contextual fibre growth to generate realistic axonal packing for diffusion MRI simulation. In: Chung, A and Gee, J and Yushkevich, P and Bao, S, (eds.) IPMI 2019: Information Processing in Medical Imaging. (pp. 429-440). Springer, Cham: Cham, Switzerland. Green open access

[img]
Preview
Text
ipmi2019_config_callaghanetal.pdf - Accepted version

Download (3MB) | Preview

Abstract

This paper presents ConFiG, a method for generating white matter (WM) numerical phantoms with more realistic orientation dispersion and packing density. Numerical phantoms are commonly used in the validation of diffusion MRI (dMRI) techniques so it is important that they are as realistic as possible. Current numerical phantoms either oversimplify the complex morphology of WM or are unable to produce realistic orientation dispersion at high packing density. The highest packing density and orientation dispersion achieved so far is only 20% at 10◦ . ConFiG takes advantage of a shift of paradigm: rather than ‘packing fibres’, our algorithm ‘grows fibres’ contextually and efficiently, attempting to produce a substrate with desired morphological priors (orientation dispersion, packing density and diameter distribution), whilst avoiding intersection between fibres. The potential of ConFiG is demonstrated by reaching the highest packing density and orientation dispersion ever, to our knowledge (25% at 35◦ ). The algorithm is compared with a ‘brute force’ growth approach showing that it is much more efficient, being O(n) compared to the O(n 2 ) brute-force method. The application of the method to dMRI is demonstrated with simulations of diffusion-weighted MR signal in three example substrates with differing orientation-dispersions, packing-densities and permeabilities.

Type: Book chapter
Title: Contextual fibre growth to generate realistic axonal packing for diffusion MRI simulation
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-20351-1_33
Publisher version: https://doi.org/10.1007/978-3-030-20351-1_33
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10077356
Downloads since deposit
7Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item