Journal
IEEE TRANSACTIONS ON MEDICAL IMAGING
Volume 40, Issue 11, Pages 2956-2964Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2021.3115547
Keywords
Tomography; image reconstruction; machine learning; artificial intelligence; deep learning; deep reconstruction
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This editorial introduces the second special issue of IEEE Transactions on Medical Imaging on deep tomographic reconstruction, highlighting the motivation, summary of included papers, and verification of shared deep learning codes. It also discusses important research topics to facilitate further investigation and collaboration in this rapidly emerging field.
As a follow-up to the first IEEE Transactions on Medical Imaging (TMI) special issue on the theme of deep tomographic reconstruction, the second special issue is assembled to reflect the status and momentum of this rapidly emerging field. In this editorial, we provide a brief background illustrating the motivation for the development of network-based, data-driven, and learning-oriented reconstruction methods, summarize the included papers, and report our verification of the shared deep learning codes. Finally, we discuss several important research topics to facilitate further investigation and collaboration.
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