Hyperpolarized 129Xe MR Image Denoising Model Based on Multimodal Edge Information

Motivation: HP 129Xe MRI is remarkably beneficial for demonstrating areas of ventilation defects in the lungs and assessing the severity of associated diseases. However, existing image denoising methods need to be improved for enhancing the detail in 129Xe MRI. Goal(s): Our goal is to improve the quality of 129Xe MRI by extracting multimodal edge information while improving the accuracy of details and edges. Approach: We propose an image denoising model that combines multimodal edge information with a multi-feature attention mechanism. Results: Compared with other models, our proposed model can effectively improve the image signal-to-noise ratio and enhance the details and edge information. Impact: Our proposed image denoising model combines multimodal edge information and uses the attention mechanism to increase the weight of important information, which effectively improves the image details and quality, and improves the help for the clinical assessment of related diseases.