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

The diagnostic quality of ultrasound scans of the same patient can vary significantly, depending on the level of skill and expertise of the person scanning the patient and the equipment used. This variation in quality can lead to patients not being diagnosed correctly, having to be recalled for a rescan or being unnecessarily referred for more invasive and costly tests. This can make diagnosis more expensive delay treatment and make hospitals inefficient. Users of ultrasound equipment are encouraged to follow guidelines about how to get the best quality scans and clinical studies have demonstrated the benefit of this approach. However, routine reviews of scan quality are not undertaken because of the the time and cost involved, so the variations in scan quality and their potentially serious consequences persist. In a collaboration between Intelligent Ultrasound Ltd and Oxford University, the AQABUS project will develop and test an automated system ("Intelligent Quality Assurance" or "IQA") for the assessment of ultrasound scan quality. IQA will provide hospitals with a means to assess scans (that is, to determine their fitness for purpose), identify staff training needs and monitor of the impact of any training undertaken. The project will require innovations that include new software to automate the analysis and scoring of ultrasound scans, and computer-based techniques of artificial intelligence known as machine learning.