Abstract #4580

Comparison of different denoising approaches for DCE-MRI

Zejun Wang¹, Bao Wang², Ziyi Huang³, Yingchao Liu⁴, and Ruiliang Bai^1,5

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

Synopsis

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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