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Erratum to: Knowledge‐driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un‐supervised learning (Magn Reson Med. 2024;92:496‐518)

Year: 2024

Type: erratum

Abstract: Due to a misunderstanding of a vendor approach to their reconstruction algorithm, the authors wish to remove the following sentence in the fifth paragraph of Section 4.4: “GE and Siemens solutions are applied to DICOM data after parallel imaging (PI) reconstruction, whereas Philips and UIH solutions attempt to build upon traditional CSPI and iterative algorithms to provide interpretability, and to fully utilize the domain specific experience and knowledge.”

Source: Magnetic Resonance in Medicine

DOI: 10.1002/mrm.30204

Authors: Shanshan Wang, Ruoyou Wu, Sen Jia, Alou Diakite, Cheng Li, Qiegen Liu, Hairong Zheng, Leslie Ying

Institutions: Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, University of Chinese Academy of Sciences, Nanchang University, University at Buffalo, State University of New York

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: bronze

OpenAlex ID: W4401037421

Cites: 1

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