Title: Registration of CT and MR image in multi-resolution framework using embedded entropy and feature fusion

Authors: Sunita Samant; Pradipta Kumar Nanda; Ashish Ghosh; Subhaluxmi Sahoo; Adya Kinkar Panda

Addresses: Image and Video Analysis Laboratory, Department of Electronics and Communication Engineering, ITER, Siksha 'O' Anusandhan, Deemed to be University, Bhubaneswar, India ' Image and Video Analysis Laboratory, Department of Electronics and Communication Engineering, ITER, Siksha 'O' Anusandhan, Deemed to be University, Bhubaneswar, India ' Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India ' Image and Video Analysis Laboratory, Department of Electronics and Communication Engineering, ITER, Siksha 'O' Anusandhan, Deemed to be University, Bhubaneswar, India ' Department of Radiology, Institute of Medical Science, Siksha 'O' Anusandhan, Deemed to be University, Bhubaneswar, India

Abstract: In this paper, a new scheme for the registration of brain CT and noisy MR images is proposed in a multi-resolution framework based on the notions of embedded entropy and nonlinear combination of the mutual information (MI) corresponding to Renyi's and Tsallis entropy. Gabor and Sobel's features are fused probabilistically and the registration is carried out in fused feature space. The weights for the fusion of the two distributions are obtained using the Bhattacharyya distance as the similarity measure. Registration parameter is obtained at different resolutions by maximising the combined mutual information obtained at different resolutions. The proposed algorithm is tested with the real patient data obtained from Retrospective Image Registration Evaluation (RIRE) database. It is found that the optimum registration parameter obtained at a low resolution of (64 × 64) has high accuracy. The proposed scheme exhibits improved performance as compared to other existing algorithms.

Keywords: multi-modal image registration; embedded entropy; mutual information; fused feature space; multi-resolution.

DOI: 10.1504/IJCVR.2024.140821

International Journal of Computational Vision and Robotics, 2024 Vol.14 No.5, pp.540 - 570

Received: 05 Jul 2022
Accepted: 10 Nov 2022
Published online: 03 Sep 2024 *

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