@inproceedings{oai:repo.qst.go.jp:00085372,
 author = {Nozaki, Hayato and Yasuhiko, Tachibana and Otsuka, Yujiro and Uchida, Wataru and Saito, Yuya and Kamagata, Koji and Aoki, Shigeki and Yasuhiko, Tachibana},
 book = {Proceedings of ISMRM 2021},
 month = {Dec},
 note = {Deep learning-based noise reduction technique for DWI contains a risk of outputting values that are greatly deviating from what it should be because of the instability problem of deep learning. The neural network model was designed in this study to suppress this risk which can fix the generated value for each pixel within the range of values of neighboring pixels in the original image. The results of the volunteer study suggested that the proposed method has potential to provide effective denoising beside suppressing the instability risk.},
 title = {Deep learning-based DWI Denoising method that suppressed the "instability" problem},
 year = {2021}
}