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Abstract #4498

Effects of computation methods, median filtering and Rician noise removal on diffusional kurtosis and tensor imaging metrics in vivo

Masaaki Hori 1,2 , Yoshitaka Masutani 3 , Ryuji Nojiri 2 , Katsutoshi Murata 4 , Koji Kamagata 1 , Mariko Yoshida 1 , Michimasa Suzuki 1 , and Shigeki Aoki 1

1 Radiology, Juntendo University School of Medicine, Tokyo, Japan, 2 Tokyo Medical Clinic, Tokyo, Japan, 3 The University of Tokyo, Tokyo, Japan, 4 Siemens Japan K.K., Tokyo, Japan

The purpose of this exhibit is to characterize, particularly for clinical use, the effects of computation methods, median filtering and Rician noise removal on diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) metrics in normal white matter and brain tumors. Median filtering is an important factor that affects quantitative diffusion metrics; for example, it changes fractional anisotropy (FA) values by 10%. Differences of computing methods and Rician noise removal appear to be less influential in changing diffusion metrics. Selection of post-processing methods should be clarified in research and clinical use.

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