Cargando…
Denoising Using Noise2Void for Low-Field Magnetic Resonance Imaging: A Phantom Study
To reduce noise for low-field magnetic resonance imaging (MRI) using Noise2Void (N2V) and to demonstrate the N2V validity. N2V is one of the denoising convolutional neural network methods that allows the training of a model without a noiseless clean image. In this study, a kiwi fruit was scanned usi...
Autores principales: | Kojima, Shinya, Ito, Toshimune, Hayashi, Tatsuya |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997543/ https://www.ncbi.nlm.nih.gov/pubmed/36908491 http://dx.doi.org/10.4103/jmp.jmp_71_22 |
Ejemplares similares
-
MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance
por: Wissmann, Lukas, et al.
Publicado: (2014) -
Fetal XCMR: a numerical phantom for fetal cardiovascular magnetic resonance imaging
por: Roy, Christopher W., et al.
Publicado: (2019) -
A phantom based laser marking workflow to visually assess geometric image distortion in magnetic resonance guided radiotherapy
por: Drobnitzky, Matthias, et al.
Publicado: (2021) -
Influence of beam hardening in dual-energy CT imaging: phantom study for iodine mapping, virtual monoenergetic imaging, and virtual non-contrast imaging
por: Kanatani, Risa, et al.
Publicado: (2021) -
Technical Note: Extended field‐of‐view (FOV) MRI distortion determination through multi‐positional phantom imaging
por: Schüler, Emil, et al.
Publicado: (2020)