Real-time stereographic rendering and display of medical images with programmable GPUs.
The study was to explore the power and feasibility of using programmable graphics processing units (GPUs) for real-time rendering and displaying large 3D medical datasets for stereoscopic display workstation. Lung cancer screening CT images were used for developing GPU-based stereo rendering and displaying. The study was run on a personal computer with a 128 MB NVIDIA Quadro FX 1100 graphics card. The performance of rendering and displaying was measured and compared between GPU-based and central processing unit (CPU)-based programming. The results indicate that GPU-based programming was capable of rendering large 3D datasets at real-time interactive rates with stereographic displays.
University of Pittsburgh, 3362 Fifth Avenue, Pittsburgh, PA 15213, United States. xwang@mail.magee.edu
Xiao Hui
XH
Wang
Walter F
WF
Good
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003196:Computer Graphics; D003199:Computer Systems; D003626:Data Display; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000295:instrumentation* / Q000379:methods; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D009716:Numerical Analysis, Computer-Assisted; D010780:Photogrammetry / Q000295:instrumentation* / Q000379:methods; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods; D014584:User-Computer Interface