Abstract
This paper describes a new non-rigid approach to register images from same- and cross-imaging modalities such as magnetic resonance imaging, computed tomography, and 3D rotational angiography. The deformation is a key challenge in medical image registration. We have proposed a diffeomorphism-based method to tackle this problem using an optimized framework. A non stationary velocity field is used to minimize the effect of forces that are derived from the image gradients. Furthermore, we propose a similarity energy function, based on the gray scale distribution, to limit the fluctuations while approaching the local minima. The proposed method is evaluated on both private and public datasets; the results show that the values of mean square error (MSE), normalized cross-correlation (NCC), structural similarity (SS), mutual information (MI), feature similarity index (FSIM), and mean absolute error (MAE) are 1.3136, 0.9962, 0.9897, 0.883, 0.9922, and 1.52± 2.09, respectively. Both qualitative and quantitative evaluation show promising registration accuracy reflecting the potential of the proposed method.
Highlights
There are different types of imaging modalities such as computed tomography (CT), ultrasound imaging (US), three dimensional rotational angiography (3DRA), and magnetic resonance imaging (MRI) that have been used by the clinicians to diagnose, plan and treat the health issue [1], [2]
The reference image includes the aneurysm vessels that appear gradually, when the contrast agent is injected in the cerebral vessels, the two images are at different time instants
The algorithm has been implemented on MATLAB R2017b running on a workstation with 16 GB RAM and 2.8 GHz Intel processor; the average time to perform registration on a data with approximately 80 slices is little more than 1 minute that is quite reasonable from clinical perspective
Summary
There are different types of imaging modalities such as computed tomography (CT), ultrasound imaging (US), three dimensional rotational angiography (3DRA), and magnetic resonance imaging (MRI) that have been used by the clinicians to diagnose, plan and treat the health issue [1], [2].
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