Deep Learning-based Noise Reduction for Fast Volume Diffusion Tensor Imaging: Assessing the Noise Reduction Effect and Reliability of Diffusion Metrics

To assess the feasibility of a denoising approach with deep learning-based reconstruction (dDLR) for fast volume simultaneous multi-slice diffusion tensor imaging of the brain, noise reduction effects and the reliability of diffusion metrics were evaluated with 20 patients. Image noise was significa...

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Detalles Bibliográficos
Autores principales: Sagawa, Hajime, Fushimi, Yasutaka, Nakajima, Satoshi, Fujimoto, Koji, Miyake, Kanae Kawai, Numamoto, Hitomi, Koizumi, Koji, Nambu, Masahito, Kataoka, Hiroharu, Nakamoto, Yuji, Saga, Tsuneo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society for Magnetic Resonance in Medicine 2020
Materias:
Technical Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922344/
https://www.ncbi.nlm.nih.gov/pubmed/32963184
http://dx.doi.org/10.2463/mrms.tn.2020-0061

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922344/
https://www.ncbi.nlm.nih.gov/pubmed/32963184
http://dx.doi.org/10.2463/mrms.tn.2020-0061

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