Title: Hybridising cuckoo search algorithm for extracting the ODF maxima in spherical harmonic representation

Authors: Mohammad Shehab; Mohammad Sh. Daoud; Hani Mahmouad AlMimi; Laith Mohammad Abualigah; Ahamad Tajudin Khader

Addresses: Computer Science Department, Aqaba University of Technology, Aqaba 77110, Jordan ' Faculty of Engineering, Al Ain University of Science and Technology, Abu Dhabi, UAE ' Faculty of Science and Information Technology, Al Zaytoonah University of Jordan, Amman, Jordan ' Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan ' School of Computer Science, Universiti Sains Malaysia, Penang, Malaysia

Abstract: The diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. Q-ball imaging (QBI) is a diffusion MRI reconstruction technique which has been proven very successful in resolving multiple intravoxel fibre orientations in MRI (i.e., fibre crossing) based on the standard computation of the orientation distribution function (ODF), which is a 3-dimension spherical function founded to detect the dominant fibre orientations in the underlying volume of a pixel (voxel). However, ODF still has a limitation in determining fibre directions which may be corrupted by neighbour directions. In this paper, we proposed a new method to solve the ODF problem by adapting the hybridisation of the cuckoo search algorithm (i.e., global search) and bat algorithm (i.e., local search), namely, CSBA. The performance of the method is demonstrated by experiments in both synthetic and real data.

Keywords: diffusion; magnetic resonance imaging; MRI; orientation distribution function; ODF; cuckoo search algorithm; CSA; bat algorithm; optimisation.

DOI: 10.1504/IJBIC.2019.103606

International Journal of Bio-Inspired Computation, 2019 Vol.14 No.3, pp.190 - 199

Received: 25 Oct 2018
Accepted: 09 Apr 2019
Published online: 13 Nov 2019 *

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