Automated life cycle processing for complex medical imaging devices

Medical imaging systems from major modalities such as Magnetic Resonance Imaging or X-Ray Computed Tomography are complex devices subject to various types of maintenance. Medical device companies that develop these systems often monitor and maintain systems sold throughout their potentially decades-...

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Bibliographic Details
Published in2017 Annual Reliability and Maintainability Symposium (RAMS) pp. 1 - 6
Main Authors Fricks, Rafael B., Trivedi, Kishor S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2017
Subjects
Biomedical imaging
Companies
Computed tomography
History
life data analysis
Maintenance engineering
mean cumulative function
non-parametric methods
R&M applications in health care
X-ray imaging
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DOI10.1109/RAM.2017.7889693

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Summary:Medical imaging systems from major modalities such as Magnetic Resonance Imaging or X-Ray Computed Tomography are complex devices subject to various types of maintenance. Medical device companies that develop these systems often monitor and maintain systems sold throughout their potentially decades-long design lives, recording a variety of maintenance operations that occur in practice. In order to interpret such massive repair record volumes collected over hundreds of distinct product lines, we present a data processing method developed for compiling maintenance histories of MRI and CT scanners. We then use the outputs of this program to compute a common non-parametric estimate, the mean cumulative function. Results are presented from active in vivo imaging product lines with identifying information omitted. Finally, key insights from the produced MCFs preface a discussion on the methods as well as future directions.
DOI:10.1109/RAM.2017.7889693