Enhancing the image quality of prostate diffusion-weighted imaging in patients with prostate cancer through model-based deep learning reconstruction

Enhancing the image quality of prostate diffusion-weighted imaging in patients with prostate cancer through model-based deep learning reconstruction

Purpose: To evaluate the utility of model-based deep learning reconstruction in prostate diffusion-weighted imaging (DWI). Methods: This retrospective study evaluated two prostate diffusion-weighted imaging (DWI) methods: deep learning reconstruction (DL-DWI) and traditional parallel imaging (PI-DWI...

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Bibliographic Details
Main Authors: Noriko Nishioka, Noriyuki Fujima, Satonori Tsuneta, Masato Yoshikawa, Rina Kimura, Keita Sakamoto, Fumi Kato, Haruka Miyata, Hiroshi Kikuchi, Ryuji Matsumoto, Takashige Abe, Jihun Kwon, Masami Yoneyama, Kohsuke Kudo
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:European Journal of Radiology Open
Subjects:
Prostate
DWI
Deep learning reconstruction
Image quality
Online Access:http://www.sciencedirect.com/science/article/pii/S2352047724000431
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