Hardware-accelerated volume and isosurface rendering based on cell-projection
Proceedings of the conference on Visualization '00
High-quality pre-integrated volume rendering using hardware-accelerated pixel shading
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware
Multidimensional Transfer Functions for Interactive Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
A Fast High Accuracy Volume Renderer for Unstructured Data
VV '04 Proceedings of the 2004 IEEE Symposium on Volume Visualization and Graphics
Towards a Medical Virtual Reality Environment for Minimally Invasive Cardiac Surgery
MIAR '08 Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality
Dynamic Model-Driven Quantitative and Visual Evaluation of the Aortic Valve from 4D CT
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Visualization and GPU-accelerated simulation of medical ultrasound from CT images
Computer Methods and Programs in Biomedicine
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In many medical imaging scenarios, real-time high-quality anatomical data visualization and interaction is important to the physician for meaningful diagnosis 3D medical data and get timely feedback. Unfortunately, it is still difficult to achieve an optimized balance between real-time artifact-free medical image volume rendering and interactive data classification. In this paper, we present a new segment-based post color-attenuated classification algorithm to address this problem. In addition, we apply an efficient numerical integration computation technique and take advantage of the symmetric storage format of the color lookup table generation matrix. When implemented within our GPU-based volume raycasting system, the new classification technique is about 100 times faster than the unaccelerated pre-integrated classification approach, while achieving the similar or even superior quality volume rendered image. In addition, we propose an objective measure of artifacts in rendered medical image based on high-frequency spatial image content.