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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