Title: Intensity-based registration of medical images

Authors: Sangeeta Sahu; Umesh Chandra Pati

Addresses: Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela-769008, India ' Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela-769008, India

Abstract: Mutual information is used widely as a similarity measure for registration of images. In order to improve the robustness of this similarity measure, spatial information is combined with normalised mutual information. In this paper, mutual information is multiplied with a gradient term to integrate spatial information with mutual information and this is taken as similarity measure. The combined measure is a good registration function. For optimisation purpose, fast convergence particle swarm optimisation technique (FCPSO) is used. In this optimisation method, the diversity of position of single particle is balanced by adding a new variable, particle mean dimension (PMD) of all particles to the existing position and velocity equation. It reduces the convergence time by reducing the number of iterations in optimisation process.

Keywords: particle mean dimension; PMD; spatial information; gradient information; entropy correlation coefficient; fast convergence PSO; particle swarm optimisation; FCPSO; intensity-based registration; medical images; CT images; computed tomography; MRI images; magnetic resonance imaging; image registration.

DOI: 10.1504/IJCVR.2016.079393

International Journal of Computational Vision and Robotics, 2016 Vol.6 No.4, pp.319 - 330

Received: 07 Jul 2014
Accepted: 26 Sep 2014
Published online: 28 Sep 2016 *

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