Medical Image Fusion via Non-Subsampled Contourlet Transform

다국어 초록 (Multilingual Abstract)

Due to the obvious advantages, the technology of medical imaging has been widely utilized in the medical areas. Commonly, the medical images of different imaging mechanism are able to guide the radiologist for the precise diagnosis of disease and for more effective interventional treatment procedures. Consequently, the fusion of different medical images of the same scene is necessary. This paper proposes a novel fusion technique for medical images based on non-subsampled contourlet transform (NSCT). Due to the better competence of image information capturing, NSCT is utilized to conduct the multi-scale and multi-directional decompositions of source images. In addition, the models of both region average energy and region coefficient deviation are used for the fusion for low-frequency sub-images and high-frequency ones, respectively. In comparison with several current typical fusion techniques, the proposed one has remarked superiorities in terms of both subjective and objective evaluations.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Non-Subsampled Contourlet Transform
• 3. Proposed Fusion Rules
• 3.1. Fusion of Low-Frequency Sub-Images
• 3.2. Fusion of High-Frequency Sub-Images
• 4. Experimental Results and Analysis
• 4.1. Experimental Condition
• 4.2. Experimental Results and Analysis
• 4.3. Discussions
• 5. Conclusion
• Acknowledgements
• References