Image-Based Needle Tracking for 3D Ultrasound Guided Interventions

Summary: 


Advances in modern imaging modalities like ultrasound (US) have evolved image-guided surgical techniques into established procedures in minimally-invasive interventions. Ultrasound is one of the most popular modalities for instrument guidance, which can provide simultaneous images of human anatomy and the tool in real time. However, ultrasound suffers from a low signal-to-noise ratio, anisotropy, imaging artifacts and the distorted appearance of medical instruments. Using an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this research, we investigate on image-processing algorithms to efficiently and robustly detect and visualize the needle in 3D US volumes for various US-guided procedures, like anesthesia and ablation.

Project Description: 
Advances in modern imaging modalities like magnetic resonance imaging, computed tomography and ultrasound (US) have evolved image-guided surgical techniques into established procedures in minimally-invasive interventions. Such interventions include biopsies, radio-frequency ablations, regional anesthesia, as well as all therapies that require the percutaneous advancing of a needle or a catheter to a target inside the patient's body. Ultrasound is one of the most popular modalities for instrument guidance, which can provide simultaneous images of human anatomy and the tool in real time using non-ionizing radiations. Moreover, the required equipment are relatively mobile and of a low cost. However, ultrasound suffers from a low signal-to-noise ratio, anisotropy, imaging artifacts and the distorted appearance of medical instruments, which impede the interpretation of the data. Furthermore, under the typically used 2D US guidance, the field of view is limited, so that any undesired movement of the instrument or US transducer may exclude parts of the tool from the image, leading to an erroneous placement. Therefore, medical specialists need considerable practicing and training to increase successful interventions and yet they may become too much focused on finding the device in the ultrasound field rather than the treatment itself.
Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. Accurate information about the position of the needle with respect to important vessel or nerve structures in the body can minimize risks to the patient and improve health outcomes. Various needle tracking systems are proposed such as robot-assisted navigation, optical needle localization, electromagnetic tracking, and photoacoustic techniques. However, they are not widely used in practice as they require additional equipment in the operating room, request specific skills to operate the additional systems and they add costs to the US system and the needle or catheter. Therefore, image-based localization techniques are more appealing for intervention support, as they can potentially overcome these limitations while the manual skills are significantly simplified after the system returns the best scan plane with respect to the needle. In this research, we investigate on image-processing algorithms to efficiently and robustly detect and visualize the needle in 3D US volumes for various US-guided procedures. The introduced methods need to maintain a balance between detection accuracy and computational complexity to permit real-time implementations for live intervention support. One proposed image-based needle localization technique is based on extraction of instrument voxels using 3D structure directions, i.e. 3D Gabor transformation and robust approximation of the tool axis. Our methods are able to successfully detect the needle with accuracy in the sub-millimetre domain. Moreover, the scan plane presented to the medical specialist always contains the instrument and its tip. Partners involve in the project are: Eindhoven University of Technology, Philips Research Eindhoven, and Catharina Hospital Eindhoven. Researchers involved are: Dr. Sveta Zinger, Ir. Arash Pourtaherian and Peter H.N de With.

This video provides examples of needle-based intervention and ultrasound imaging of the intervention needle.

Application Area: 
Healthcare
Video/Imaging Discipline: 
3D processing
Partners: