Rapid voxel classification methodology for interactive 3D medical image visualization.
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.
Zhang
Qi
Q
Imaging Research Laboratories, Robarts Research Institute, Biomedical Engineering, University of Western Ontario, London, Ontario N6A 5K8, Canada. qzhang@imaging.robarts.ca
Eagleson
Roy
R
Peters
Terry M
TM
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003199:Computer Systems; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface