Summary
Volume rendering is a computationally intensive discipline that has become invaluable for visualizing large volumes of data in a wide variety of fields, including medical, dental, industrial, geoscience and bioscience.
General Information
Volume rendering, also called direct volume rendering, is a set of techniques used to visualize a 2D projection of a 3D discretely sampled data set, typically a 3D scalar field.
The volume rendering technique is determined by the rendering equation. In volume rendering, ray casting is an image-based technique, because the computation originates from the output image and not the input volume data. Ray casting utilizes only the primary rays. A ray is generated for each pixel within the selected image area. The ray is clipped at the volume’s boundaries, and then sampled at regular or adaptive intervals within the volume.
Color and opacity data are accumulated for each ray. A transfer function interpolates the data at each sample point. Transfer function based rendering modes produce colored 3D volume renderings with translucent, transparent and opaque effects. The transfer function maps a voxel's Hounsfield value (or other dataset unit) to three components: color, lighting and opacity values. When rays are cast through the volume, they are differentially absorbed and colored by the voxels through which they pass, based on these three components.
Although volume rendering plays a key role in many important fields, several technical challenges need to be overcome to assure wide deployment of the direct volume rendering technique. First, volume rendering is a computationally expensive process. In order to produce a high quality two-dimensional image that can capture the three-dimensional characteristics of a 3D target, volume rendering usually requires a substantial number of calculations to process large 3D datasets. For example, using conventional direct volume rendering algorithms, at least 140 million calculations are required to generate a 2D image of 5122 pixels, for a typical 3D dataset of 5123 voxels.
Moreover, many applications require real-time volume rendering of a 3D dataset, so that a user can view successive two-dimensional images of the 3D dataset from different viewing angles or visualization parameters, without a significant delay. In medical imaging, it is generally accepted that a sequential 2D image rendering of at least six frames per second meets the need for real-time interactive feedback. This is equivalent to nearly 1 billion calculations per second.
More efficient algorithms have been developed to reduce the computational cost of volume rendering. However, many of these algorithms achieve their efficiency by sacrificing the quality of the generated 2D images. For example, a common problem with discrete representation of a continuous object is the jitter effect, which is most obvious when a user zooms in to view more details of the continuous object. If the jitter effect is not carefully controlled, it may significantly corrupt the quality of an image generated by a direct volume rendering algorithm.
In response to these challenges, Fovia has developed a volume rendering method and system that increases the rendering efficiency with minimal or imperceptible impact on the image quality.
In healthcare, three-dimensional imaging is a valuable tool for optimizing minimally invasive surgery and therapy outcomes, eliminating unnecessary tests and treatments, accelerating diagnoses and augmenting clinical decision-making insights. An expanding workload must now be completed with the same or fewer resources, driven in part by overall cost pressures in the healthcare system, the high cost of imaging equipment and a shortage of radiologists. Accelerating the speed of image interpretation is essential for improving workflow productivity, and avoiding bottlenecks caused by the large number of images being generated. Therefore, to reduce costs and improve the quality of service, a clear need exists for efficient, high quality advanced visualization tools like Fovia’s High Definition Volume Rendering.
High Definition Volume Rendering® (XStream® HDVR®) Information
Fovia’s CPU-based XStream® HDVR® technology successfully overcomes today’s challenges through its proprietary, volumetric ray-tracing algorithms that use deep super-sampling to achieve superior interactive quality and performance. XStream HDVR minimizes computational costs, and its thin client-server architecture can be deployed worldwide anytime, anywhere. XStream HDVR is server-based and uses streaming .jpgs to delivery high fidelity imaging to any off-the-shelf client computer or device worldwide. XStream HDVR enables remote rendering and can also be utilized locally, on local networks, or via the cloud.
Fovia’s unparalleled quality, coupled with the unique high-performance algorithms of High Definition Volume Rendering®, make Fovia a world leader in 3D volumetric rendering.
Visit the XStream HDVR Advantage and XStream HDVR Product Line pages for more information on Fovia’s High Definition Volume Rendering®
