Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis

Shehata, Mostafa A; Saad, Abdelrahman M.; Kamel, Serageldin; Stanietzky, Nir; Roman-Colon, Alicia M; Morani, Ajaykumar C; Elsayes, Khaled M.; Jensen, Corey T

doi:10.1007/s00261-023-03966-2

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Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis

Author(s): Mostafa A. Shehata , Abdelrahman M. Saad , Serageldin Kamel , Nir Stanietzky , Alicia M. Roman-Colon , Ajaykumar C. Morani , Khaled M. Elsayes , Corey T. Jensen

Publication date Created: August 2023

Publication date (Electronic): June 06 2023

Journal: Abdominal Radiology

Publisher: Springer Science and Business Media LLC

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Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

Motonori Akagi, Yuko Nakamura, Toru Higaki … (2019)

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Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.

Joel Greffier, Aymeric Hamard, Fabricio Pereira … (2020)

To assess the impact on image quality and dose reduction of a new deep learning image reconstruction (DLIR) algorithm compared with a hybrid iterative reconstruction (IR) algorithm.