High-quality cardiac image dynamic visualization with feature enhancement and virtual surgical tool inclusion

Traditional approaches for rendering segmented volumetric data sets usually deliver unsatisfactory results, such as insufficient frame rate, low image quality, and intermixing artifacts. In this paper, we introduce a novel “color encoding” technique, based on graphics processing unit (GPU) accelerated raycasting and post-color attenuated classification, to address this problem. The result is an algorithm that can generate artifact-free dynamic volumetric images in real time. Next, we present a pre-integrated volume shading algorithm to reduce graphics memory requirements and computational cost when compared to traditional shading methods. We also present a normal-adjustment technique to improve image quality at clipped planes. Furthermore, we propose a new algorithm for color and depth texture indexing that permits virtual solid objects, such as surgical tools, to be manipulated within the dynamically rendered volumetric cardiac images in real time. Finally, all these techniques are combined within an environment that permits real-time visualization, enhancement, and manipulation of dynamic cardiac data sets.