Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction
Author:
Affiliation:
1. From the Department of Radiology, Cincinnati Children’s Hospital Medical Center, 3333, Burnet Ave, Cincinnati, OH 45329; and Department of Radiology, University of Cincinnati Medical School, Cincinnati, Ohio.
Publisher
Radiological Society of North America (RSNA)
Subject
Radiology, Nuclear Medicine and imaging
Link
http://pubs.rsna.org/doi/pdf/10.1148/radiol.2020202317
Reference34 articles.
1. Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective
2. Impact of iterative reconstruction on CNR and SNR in dynamic myocardial perfusion imaging in an animal model
3. Model-based Iterative Reconstruction: Effect on Patient Radiation Dose and Image Quality in Pediatric Body CT
4. Image quality with iterative reconstruction techniques in CT of the lungs—A phantom study
5. Towards task-based assessment of CT performance: System and object MTF across different reconstruction algorithms
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