2019
DOI: 10.1016/j.mri.2018.11.022
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Denoising of MR images using Kolmogorov-Smirnov distance in a Non Local framework

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Cited by 29 publications
(10 citation statements)
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“…To investigate the correlation of age, gender and disease severity with antibody dynamic pattern, the test results were classified and the data were fitted by the software R. Further, the Kolmogorov-Smirnov test (Manoel et al 1996), which is a nonparametric test of the equality of continuous, one-dimensional probability distribution, is employed to quantify the level similarity of the antibody dynamics among the comparison groups, including both antibody level (distance) and distribution pattern (P-value) during convalescence. The smaller K-S distance derived from Cumulative Distribution Functions among subgroups is equal to the measurement of their similarity of titer (Baselice et al 2019). The test results indicate the distribution pattern is positively correlated to the distance value.…”
Section: Antibody Titermentioning
confidence: 90%
“…To investigate the correlation of age, gender and disease severity with antibody dynamic pattern, the test results were classified and the data were fitted by the software R. Further, the Kolmogorov-Smirnov test (Manoel et al 1996), which is a nonparametric test of the equality of continuous, one-dimensional probability distribution, is employed to quantify the level similarity of the antibody dynamics among the comparison groups, including both antibody level (distance) and distribution pattern (P-value) during convalescence. The smaller K-S distance derived from Cumulative Distribution Functions among subgroups is equal to the measurement of their similarity of titer (Baselice et al 2019). The test results indicate the distribution pattern is positively correlated to the distance value.…”
Section: Antibody Titermentioning
confidence: 90%
“…Fabio. B et al, in [17] introduced a novel sparse tensor model based on the weighted regularization from MRI with efficient computation. The method uses brain MR images for the study with 512 X 512 with 20 slices.…”
Section: Related Workmentioning
confidence: 99%
“…This proposed method preserves the structural relations between the magnetic resonance image series. A filtering technique based on distance algorithm [19] is proposed with a cumulative distribution function of different pixels and compared the similarities with different acquisition parameters. Similar pixel values are fused to produce the resultant output then the method is compared with local and non-local methods, but the computational time is more compared to other techniques.…”
Section: Literature Reviewmentioning
confidence: 99%