Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
http://link.springer.com/content/pdf/10.1007/s00330-020-06724-w.pdf
Reference35 articles.
1. Brenner DJ, Hall EJ (2007) Computed tomography--an increasing source of radiation exposure. N Engl J Med 357:2277–2284
2. Greffier J, Pereira F, Macri F, Beregi JP, Larbi A (2016) CT dose reduction using automatic exposure control and iterative reconstruction: a chest paediatric phantoms study. Phys Med 32:582–589
3. Beregi JP, Greffier J (2019) Low and ultra-low dose radiation in CT: opportunities and limitations. Diagn Interv Imaging 100:63–64
4. Greffier J, Frandon J, Larbi A, Beregi JP, Pereira F (2019) CT iterative reconstruction algorithms: a task-based image quality assessment. Eur Radiol. https://doi.org/10.1007/s00330-019-06359-6
5. Willemink MJ, Noel PB (2019) The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence. Eur Radiol 29:2185–2195
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