体素
聚类分析
灌注
核医学
滤波器(信号处理)
动能
医学
放射科
计算机科学
物理
人工智能
计算机视觉
量子力学
作者
Zixiang Chen,Yuxi Jin,Zhenxing Huang,Na Zhang,Kaiyi Liang,Guotao Quan,Dong Liang,Hairong Zheng,Zhanli Hu
出处
期刊:IEEE transactions on radiation and plasma medical sciences
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-1
标识
DOI:10.1109/trpms.2024.3402272
摘要
Dynamic cerebral perfusion CT (PCT) is an effective imaging technique for the clinical diagnosis and therapy guidance of many kinds of cerebrovascular diseases (CVDs), but the large radiation dose imposed on a patient during repeated CT scans greatly limits its clinical applications. Achieving low-dose PCT imaging with the help of advanced and satisfactory imaging methods is needed. A kinetic-induced voxel-clustering filter (KVCF) is proposed in this work to help process noisy and distorted PCT images acquired from low-dose CT scan protocols. In this new method, the intrinsic kinetic information of objective PCT images is extracted and effectively utilized to construct an image filter for every PCT frame. The new method is validated using both simulated and clinical low-dose PCT data, and the peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) are applied for quantitative evaluations of both the dynamic images and the calculated hemodynamic parametric maps. Compared to several existing methods, the proposed KVCF method produces the best qualitative and quantitative imaging effects. With satisfactory performance and high interpretability, KVCF is proven to be effective and implementable in clinical low-dose PCT imaging tasks.
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