摘要
目的:改善高加速倍数下弥散加权成像的图像重建质量,从而实现加速采集。方法:利用图像块匹配的方法提取弥散图像内相似的图像块,进行低秩特性约束和稀疏约束,随后将其与传统的敏感度编码(SENSE)并行重建算法相结合来改善图像重建质量,降低图像噪声。实验采集两组人体数据,分别比较3倍加速和4倍加速下传统的SENSE重建、基于总变分约束的SENSE(SENSE-TV)重建以及本文方法的重建效果,定量分析弥散图像以及各向异性分数(FA)图与全采样的参考图像的误差。结果:在3倍加速和4倍加速采集下,本文方法均比传统的SENSE、SENSE-TV方法重建的弥散图像质量更好,定量分析的参数FA值更精确,误差更低。结论:利用图像内相似性图像块的低秩特性和稀疏特性约束图像重建,有望实现高加速倍数下的高质量成像。
Objective To improve the image reconstruction quality of diffusion-weighted imaging with high acceleration factor for accelerating the acquisition.Methods Image block matching method was used to extract similar image blocks in diffusionweighted images for low-rank constraint and sparseness constraint,and it was integrated into the traditional sensitivity encoding(SENSE)parallel reconstruction algorithm to improve image reconstruction quality and reduce image noise.Two sets of human data were collected in the experiments.The reconstructed results using traditional SENSE reconstruction,total variation constraint-based SENSE(SENSE-TV)reconstruction and the proposed method were compared at 3×and 4×accelerations.The errors of the diffusion images and fractional anisotropy(FA)maps with the reference images from fully sampled data were quantitatively calculated.Results Compared with traditional SENSE and SENSE-TV methods,the proposed method resulted in the reconstructed diffusion images with higher image quality and lower image errors in the 3×and 4×acceleration experiments.The quantitative analysis showed that the FA calculated by the proposed method was more accurate and had lower errors.Conclusion By constraining low-rank and sparseness of similar image blocks from images in reconstruction,it is expected to achieve high image quality under high acceleration factor.
作者
徐中标
邓官华
黄唯
XU Zhongbiao;DENG Guanhua;HUANG Wei(Department of Radiation Oncology,Guangdong Provincial People's Hospital(Guangdong Academy of Medical Sciences),Southern Medical University,Guangzhou 510080,China)
出处
《中国医学物理学杂志》
CSCD
2024年第10期1237-1242,共6页
Chinese Journal of Medical Physics
基金
国家自然科学基金(62101144)。
关键词
弥散加权成像
图像重建
块匹配
图像约束
diffusion-weighted imaging
image reconstruction
block matching
image constraint
