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In Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine

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 significantly decreased with dDLR. Although fractional anisotropy (FA) of deep gray matter was overestimated when the number of image acquisitions was one (NAQ1), FA in NAQ1 with dDLR became closer to that in NAQ5.

Sagawa Hajime, Fushimi Yasutaka, Nakajima Satoshi, Fujimoto Koji, Miyake Kanae Kawai, Numamoto Hitomi, Koizumi Koji, Nambu Masahito, Kataoka Hiroharu, Nakamoto Yuji, Saga Tsuneo


denoising approach with deep learning-based reconstruction, diffusion tensor imaging, diffusion tensor tractography, number of image acquisition