Speaker: Åsmund Birkeland
Ultrasound is one of the most frequently used imaging modalities in modern medicine. The high versatility and availability of ultrasound workstations is applied in various medical scenarios, such as diagnosis, treatment planning, intra-operative imaging, and more. Modern ultrasound workstations provide live imaging of anatomical structures, as well as physiological processes, such as blood flow. However, the imaging technique have a high presence of noise, a small scan sector, and are much affected by attenuation artefacts. Thus, traditional techniques for segmentation and visualization are not applicable to ultrasound data.
In this talk, we present our latest advancements in segmentation and visualization techniques, tailored specifically for the characteristics of ultrasound data. We present new methods for interactive vessel segmentation for both 3D freehand and 4D ultra-sound. By directly involving the examiner in the segmentation approach as well as combining data from different probe viewpoints, we are able to obtain 3D models of blood vessels rapidly and robustly.
With the ability of robust vessel extraction, we introduce novel visualization techniques which utilize the previously acquired 3D vessel models. For anatomical imaging, we present a new physics-based approach for volume clipping, enhanced slice rendering and even defining curved Couinaud-surfaces. The technique creates a deformable membrane to adapt to structures in the underlying data, defined either by predefined segmentation, iso-values, or other data attributes.
For functional imaging, medical ultrasound can use the Doppler principle to image blood flow. However, Doppler ultrasound only measures a projected velocity magnitude of the data. In this talk, we present a technique that uses the direction of the blood vessels in order to reconstruct 3D blood flow from Doppler ultrasound. By extending Doppler ultrasound with this directional information, we are able to apply traditional flow visualization techniques for displaying the blood flow. Finally, we investigated the usage of moving particles as a means to depict velocity in flow visualization. Based on a series of studies targeted for motion perception, we present a new compensation model to correct for distortions in the human visual system. This model can help users to make a more consistent estimation of velocities from evaluating the motion of particles.