Automating quality assessment of B-mode ultrasound scans (AQABUS)

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Diagnostic quality of ultrasound (US) scans of the same patient can vary significantly, depending on the level of skill andexpertise of the sonographer and the equipment used. This well documented operator dependence of quality can lead tomisdiagnosis; unnecessary referrals to other imaging modalities; rescans; and results in inefficiencies in clinical workflowwith associated added healthcare costs.In order to avoid the resultant delayed or incorrect stratification, sonographers are encouraged to follow standardisedacquisition protocol guidelines. Clinical studies show the benefit of this. However, no systematic image reviews areundertaken. This lack of standardization and monitoring of conformance has implications for the quality of diagnosis andclinical decisions made in a health service, and is also a key barrier to wider adoption of US as a cost-effective technologyfor stratified medicine.In a collaboration between Intelligent Ultrasound Ltd and Oxford University, the AQABUS project proposes to develop andevaluate a technology platform for automated quality assessment of US scans. The solution will be delivered as a QualityAssurance Service (QAS) to imaging departments, to assess whether scans are fit for purpose. Innovations includecreation of the IT infrastructure for delivering such a service; clinical design of QA reporting; and machine learning toautomate image QA which is key to the business proposition.