GPU-Based Visualization and Synchronization of 4-D Cardiac MR and Ultrasound Images

Abstract

In minimally invasive image-guided interventions, different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and 3-D ultrasound (US), can provide complementary, multispectral image information. Dynamic image registration is a well-established approach that permits real-time diagnostic information to be enhanced by placing lower-quality real-time images within a high quality anatomical context. For the guidance of cardiac interventions, it would be valuable to register dynamic MRI or CT with intra-operative US. However, in practice, either the high computational cost prohibits such real-time visualization, or else the resulting image quality is not satisfactory for accurate interventional guidance. Modern graphics processing units (GPUs) provide the programmability, parallelism and increased computational precision to address this problem. In this paper, we first outline our research on dynamic 3-D cardiac MR and US image acquisition, real-time dual-modality registration and US tracking. Next, we describe our contributions on image processing and optimization techniques for 4-D (3-D + time) cardiac image rendering, and our GPU-accelerated methodologies for multimodality 4-D medical image visualization and optical blending, along with real-time synchronization of dual-modality dynamic cardiac images. Finally, multiple transfer functions, various image composition schemes, and an extended window-level setting and adjustment approach are proposed and applied to facilitate the dynamic volumetric MR and US cardiac data exploration and enhance the feature of interest of US image that is usually restricted to a narrow voxel intensity range.