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FORNY20-FORNY2020

KVAL: Software for real-time registration of ultrasound to CT images

Alternative title: Programvare for registrering av ultralyd og CT bilder

Awarded: NOK 0.50 mill.

Project Number:

340808

Project Period:

2022 - 2023

Funding received from:

Medical ultrasound is a safe imaging modality with relatively inexpensive and easily portable equipment. As opposed to other modalities that require patient transportation to a dedicated examination room (e.g., CT and MR), ultrasound can be used bedside. Ultrasound imaging is therefore widely accessible and used for many medical applications. Downsides include that the ultrasound field of view is limited and therefore provides a reduced overview of the patient’s anatomy, image quality is sometimes poor, and both acquisition and interpretation of images are operator dependent and require a high degree of expertise. For several clinical applications, CT or MR images from a prior examination is already available at the time of ultrasound imaging. Being able to combine these images with information from ultrasound in real-time during the ultrasound exam could be of huge benefit, both for diagnostic purposes and for guidance of minimally-invasive therapy. Combining information from several image sources is referred to as image-fusion. A key to image-fusion is to determine the spatial relationship between images defined in different coordinate systems and with different resolution. Methods devised to find this relationship are known as registration methods, and has been a long-term research focus in SINTEF Health Research. This functionality is available on several high-end commercial ultrasound scanners, but current solutions require manual landmark selection for registration, and are therefore quite labour intensive. We have therefore developed an automatic, real-time method that has the potential to increase accuracy, reduce time and labour, and open for increased use of image fusion by more operators and for new applications. Through this project, we have established a good overview of already available commercial methods within various clinical application areas, and looked more closely at the potential of our method. Based on what is commercially available already, and the properites of our technological solution, we have concluded not to proceed with our method as a general solution for many different application areas. However, it will be interesting to further develop the method towards some limited clinical tasks in interventional radiology. The commercial potential is then more limited, but may be interesting as an integral part of a larger system for guiding interventions.

The outcome of the project is that we have established a good overview of already available commercial methods within various clinical application areas, and looked more closely at the potential of our method. Based on what is commercially available already, and the properties of our technological solution, we have concluded not to proceed with our method as a general solution for many different application areas. However, it will be interesting to further develop the method towards some limited clinical tasks in interventional radiology. The commercial potential is then more limited, but may be interesting as an integrated part of a larger system for image-guided interventions.

Funding scheme:

FORNY20-FORNY2020