Abstract
The diversity and complexity of cardiac tissues makes it very challenging to visualize 3D cardiac magnetic resonance image (MRI) data. In this paper, we proposed an adaptive volume data preprocessing approach, and used a semi-automated transfer function for volume rendering of the pre-processed cardiac MRI data. To improve the quality of 3D cardiac MRI data, we first used a three-dimensional median filtering method for data denoising, and then proposed an adaptive ellipsoidal Gaussian filtering scheme for local-feature-preserving data smoothing. For effective visualization, we implemented a volume rendering pipeline with ray casting and the semi-automated transfer function design scheme, which allow user create transfer function to visualize the information which he is interested in. Finally, the efficiency of the proposed 3D cardiac MRI data visualization method is verified using the sheep heart MRI data.
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