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. 2018 Jun 11;8:8849. doi: 10.1038/s41598-018-27260-0

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© The Author(s) 2018

Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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The automated quantification of intraplaqueneovasculization (IPN) of carotid plaque using QontraXt. (A) A manual region of interest (ROI) was placed to enclose the whole area of the plaque with IPN demonstrated in the plaque ROI (arrow). (B) Parametric imaging: Parametric imaging results into four images that corresponds to the maps of the curve fitting parameters. (C) The time-intensity curve (green-colored curve). (D) Parametric fitting curve: time-intensity fitting curve (blue curve). Numeric values of peak, TP, sharpness, and AUC were automatically calculated based on the time-intensity curve and are shown at the top of the graphs.