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Abstract #4580

Comparison of different denoising approaches for DCE-MRI

Zejun Wang1, Bao Wang2, Ziyi Huang3, Yingchao Liu4, and Ruiliang Bai1,5
1Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China, 2Department of Radiology, Qilu Hospital of Shandong University, Jinan, China, 3College of Life Sciences, Zhejiang University, Hangzhou, China, 4Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China, 5Department of Physical Medicine and Rehabilitation, Interdisciplinary Institute of Neuroscience and Technology, The Affiliated Sir Run Run Shaw Hospital, School of Medicine,, Zhejiang University, Hangzhou, China


The physiological parameters estimated from pharmacokinetic modeling of DCE-MRI are usually biased by the non-white, spatially-dependent noise. In this study, we compared several state-of-arts denoising approaches, including gaussian low pass filter (GLPF), the dynamic nonlocal mean (DNLM), the nonlocal mean based on spatiotemporal patches (NLM-ST), 2D and 3D kinetics-induced bilateral filter (KIBF). Our results reveal that the 3D KIBF can reduce the noise significantly and reserve subtle information best.

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