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Image Analysis for Ultrasound Quality Assurance
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The quality assurance (QA) of ultrasound transducers is often identified as an area requiring continuous development in terms of the tools available to users. Periodic evaluation of the transducers as part of the QA protocol is important, since the quality of the diagnostics. Some of the key criteria determining the process of developing a QA protocol include the complexity of setup, the time required, accuracy, and potential automation to achieve scale. For the current study, a total of eight different ultrasound machines (12 transducers) with linear transducers were obtained separately. The results from these 12 transducers were used to validate the protocol. WAD-QC was used as part of this study to assess in-air reverberation patterns obtained from ultrasound transducers. Initially, three in-air reverberation images obtained from normal transducers and three obtained from defective transducers were used to calculate the uniformity parameters. The results were applied to 12 other images obtained from independent sources. Image processing results with WAD-QC were verified with imageJ. A comparison of raw data for uniformity showed consistency, and using controls based on mean absolute deviation yielded identical results. WAD-QC can be considered as a powerful mechanism for quick, efficient, and accurate analysis of in-air reverberation patterns obtained from ultrasound transducers.
Title: Image Analysis for Ultrasound Quality Assurance
Description:
The quality assurance (QA) of ultrasound transducers is often identified as an area requiring continuous development in terms of the tools available to users.
Periodic evaluation of the transducers as part of the QA protocol is important, since the quality of the diagnostics.
Some of the key criteria determining the process of developing a QA protocol include the complexity of setup, the time required, accuracy, and potential automation to achieve scale.
For the current study, a total of eight different ultrasound machines (12 transducers) with linear transducers were obtained separately.
The results from these 12 transducers were used to validate the protocol.
WAD-QC was used as part of this study to assess in-air reverberation patterns obtained from ultrasound transducers.
Initially, three in-air reverberation images obtained from normal transducers and three obtained from defective transducers were used to calculate the uniformity parameters.
The results were applied to 12 other images obtained from independent sources.
Image processing results with WAD-QC were verified with imageJ.
A comparison of raw data for uniformity showed consistency, and using controls based on mean absolute deviation yielded identical results.
WAD-QC can be considered as a powerful mechanism for quick, efficient, and accurate analysis of in-air reverberation patterns obtained from ultrasound transducers.
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