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Abstract #3547

Usefulness of Deep Learning Based Denoising Method for Compressed Sensing in Pituitary MRI

Takeshi Nakaura1, Hiroyuki Uetani1, Kousuke Morita1, Kentaro Haraoka2, Akira Sasao1, Masahiro Hatemura1, and Toshinori Hirai1
1Diagnostic Radiology, Kumamoto University, Kumamoto, Japan, 2Cannon Medical Systems Japan, Tochigi, Japan

We evaluated image quality of hybrid type deep learning reconstruction (hybrid-DLR) with wavelet based denoising method in T2-weighted images (T2WI) of the pituitary with various denoising level (1-5). There was a progressive increase in SNR with hybrid-DLR with increase of the denoising level. On the other hand, the SNR of conventional wavelet-based method was not increased at high denoising levels (4-5). All qualitative scores of hybrid-DLR in any denoising levels are higher than that of wavelet based denoising method, and the difference became more noticeable at higher denoising levels.

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