Automated daily quality control analysis for mammography in a multi-unit imaging center

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http://hdl.handle.net/10138/310064

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Sundell , V-M , Mäkelä , T , Meaney , A , Kaasalainen , T & Savolainen , S 2019 , ' Automated daily quality control analysis for mammography in a multi-unit imaging center ' , Acta Radiologica , vol. 60 , no. 2 , pp. 140-148 . https://doi.org/10.1177/0284185118776502

Title: Automated daily quality control analysis for mammography in a multi-unit imaging center
Author: Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli
Contributor: University of Helsinki, Department of Physics
University of Helsinki, Department of Diagnostics and Therapeutics
University of Helsinki, Department of Mathematics and Statistics
University of Helsinki, Department of Diagnostics and Therapeutics
University of Helsinki, Department of Physics
Date: 2019-02
Language: eng
Number of pages: 9
Belongs to series: Acta Radiologica
ISSN: 0284-1851
URI: http://hdl.handle.net/10138/310064
Abstract: Background: The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose: To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods: An automated image quality analysis software using the discrete wavelet transform and multi-resolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results: The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion: Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.
Subject: Mammography
quality assurance
image quality
ACR phantom
ACCREDITATION PHANTOM
PERFORMANCE
114 Physical sciences
3126 Surgery, anesthesiology, intensive care, radiology
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