Computed Tomography slice interpolation in the longitudinal direction based on deep learning techniques: To reduce slice thickness or slice increment without dose increase

Computed Tomography slice interpolation in the longitudinal direction based on deep learning techniques: To reduce slice thickness or slice increment without dose increase

Large slice thickness or slice increment causes information insufficiency of Computed Tomography (CT) data in the longitudinal direction, which degrades the quality of CT-based diagnosis. Traditional approaches such as high-resolution computed tomography (HRCT) and linear interpolation can solve thi...

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Bibliographic Details
Main Authors: Shuqiong Wu, Megumi Nakao, Keiho Imanishi, Mitsuhiro Nakamura, Takashi Mizowaki, Tetsuya Matsuda
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754169/?tool=EBI

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754169/?tool=EBI

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