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. 2022 Aug 13;39(1):221–231. doi: 10.1007/s10554-022-02703-y

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — CAC detection for FBP, HIR, MBIR and DLR for one of the patients. Window width (WW) and window level (WL) setting were constant for the upper row: WW = 380, WL = 40. The bottom row shows subtraction images between FBP and HIR, MBIR and DLR. For MBIR, overall CAC quantification increases with respect to FBP. FBP filtered back projection, HIR hybrid iterative reconstruction, MBIR model-based iterative reconstruction, DLR deep learning-based reconstruction