Ultrasonography (US) is a versatile, non-invasive, portable, widely available and affordable technology compared to other equivalent technologies, playing a relevant role in ambulatory care and a preferred diagnostic tool. It also allows faster and safer results but the acquisition of images for diagnosis has several limitations.
Current clinical procedures require highly specialised professionals to position an US probe, who often accumulate high workloads caused by lack of qualified human resources, high patient flow and emotional stress arising from patient interaction. About 90% of these professionals report complaints related to occupational health aspects (e.g. musculoskeletal disorders; visual disorders and eye fatigue; burnout syndrome, anxiety and emotional frustration).
ARGUS is defined as an autonomous robotic system that will serve as a support tool for the medical professional and will encompass the definition of operation modes:
3) autonomous navigation.
These modes will support the various tasks to be performed during an US diagnostic clinical procedure. The ARGUS system will also be able to learn a given procedure and subsequently replicate it with the accuracy and quality required for diagnosis, with minimal practitioner involvement.
ARGUS will automatically assess the quality of the US images acquired in real time, generating feedback from the image that will be used to automatically adjust: the robot posture and probe contact force. Thus it will be possible to guarantee a high quality acquisition, necessary for a correct diagnosis. The processing and segmentation of the medical image will also be automatic and will allow to evaluate the potentiality of computational decision-aided diagnosis by classification of anatomical structures and masses present in abdominal US images.
The main goal of ARGUS will be the automation and optimization of the US images acquisition procedure which will allow:
1) reduction of the professionals' workload, reducing the examination time and the need to perform repetitive tasks;
2) increase of the diagnostic accuracy, making the procedure robust and independent of the operator and his experience;
3) extension of the access to qualified medical service of excellence to geographically remote, unattended and hard to reach areas.
Development and validation in clinical environment of a proof of concept for automating ultrasound diagnostic procedures.