INHUD: Intelligent Handheld Ultrasound Device

Handheld ultrasound offers practical and cost-effective diagnostic imaging to health professionals working in areas that today are not using ultrasound. One of the main reasons adoption of ultrasound is low among general practitioners, paramedics, physiotherapists, in emergency room or nursing homes, is the amount of training required to efficiently use ultrasound clinically. This project aim to develop solutions that can reduce the amount of training required by developing good visual solutions that can assist new ultrasound users in the efficient use of handheld ultrasound. The solutions are aimed towards both localizing organs and highlighting clinical features in the ultrasound image that are relevant for diagnosis. The project has to a large extent used new artificial intelligence methods. More specifically, the project has evaluated solutions using both ultrasound images and sensor data from inertial measurement units as input to the AI models, and how the models can run on mobile devices (phones, tablets) with a wireless connection to a handheld ultrasound device. The project has demonstrated a proof of concept on how artificial intelligence can be integrated in a mobile app for ultrasound examinations. The same proof of concept has been used to demonstrate use of artificial intelligence to automate image quality testing of the ultrasound scanner in manufacturing, in order to achieve cost effective manufacturing with reliable product quality. A functional prototype has been developed that is demonstrating a solution to assist inexperienced users during an ultrasound exam. The solution simplifies the understanding of where in the 3-dimensional space the shown 2D ultrasound image is acquired, and where the ultrasound probe is positioned. The project has also demonstrated visual solutions that highlights clinically relevant data in both 2D images and in 3D volume reconstructions.

GE Vingmed Ultrasound have significantly strengthened the position in the global handheld ultrasound market. Independent sources indicate GE HealthCare is now market leader in handheld ultrasound (https://www.linkedin.com/posts/rezazahiri_handheld-ultrasound-market-activity-7134994789237755905-fDVG), and GE Vingmed Ultrasound is the main design center for handheld ultrasound within GE HealthCare. Two major product introductions during the projects lifetime incorporating parts of the program results have formed the basis for important feature additions in these product introductions. The results from the project has the potential to enable really efficient collaboration with teams within and outside of GE Healthcare, which will bring new clinical solutions to the handheld products at a relatively high pace in the years to come. It is also anticipated that the results from the project will significantly contribute to enhanced ultrasound guidance solutions in coming product updates.

Creating images of the interior of the human body is a crucial ingredient to modern medical diagnostics. Unfortunately, equipment for such medical imaging is typically bulky and expensive to buy, operate, and maintain. At points where care is given most frequently, such as at the general practitioner’s office, in an ambulance, emergency room, or a nursing home, medical imaging is therefore largely absent today. While small, portable ultrasound scanners could revolutionize this situation and bring affordable and side-effect-free ultrasound to the point of care, widespread adoption of such devices has not happened yet. This is mostly due to the large amount of training required to confidently operate ultrasound scanners, which poses an unreasonable investment for less experienced, occasional users. The vision of this project is to create an Intelligent Hand-held Ultrasound Device – INHUD – that visually assists healthcare professionals with little or no ultrasound experience in the device’s operation and in their clinical decision making. Our ambition is to offer a new hand-held imaging solution which opens the door to ultrasound for occasional users and provides significantly increased productivity and diagnostic confidence also for more experienced ones. The most important R&D challenges we together with our partner SINTEF expect to address in this project are - to gain a spatial understanding of the scanned area, - to perform intelligent full-body anatomy labelling in scanned ultrasound images, - to intelligently visualize regions of medical interest, - to provide visual aid for probe handling to the user, - and to do all that without noticeable lag with respect to probe movement. - to utilize the developed labeling technology to gain productivity in the manufacturing environment by implementing more efficient system test procedures based on artificial intelligense.