We propose a general and unified framework to harness the abundant performance of current and future generation commodity graphics hardware (GPUs) for the purpose of tomographic reconstruction from projections. Preliminary results indicate that a performance improvement on the order of 1-2 magnitudes over traditional CPU-based approaches can be obtained. To proof and ensure the generality of our framework and approach, our proposal will address the reconstruction from a diverse set of raw data (such as kV X-rays, MV X-rays, and protons), with a diverse set of reconstruction algorithms (such as maximum likelihood algorithms, algebraic methods, and Feldkamp-style filtered backprojection), and within a diverse set of application scenarios (such as CT, SPECT, PET, and Proton CT). Starting from the basic reconstruction operators, we will model all dominant physical and algorithmic effects that occur in radiation-based tomography, such as depth weighting, detector geometric response, attenuation weighting, and scatter compensation, using implementations that map optimally to the graphics hardware and take full advantage of its computational architecture. The rapid speeds of reconstruction will also enable a new concept that we call Visual Reconstruction Steering (VRS). This VRS framework will consist of a visual interface in which users can build and interactively control reconstructions as they occur on the GPU, and in which they can visualize and assess the results in real time. Our research results, all software, and documentation will be disseminated via a dedicated website, www.Rapid-CT.org.
| Zheng, Ziyi; Xu, Wei; Mueller, Klaus (2010) VDVR: verifiable visualization of projection-based data. IEEE Trans Vis Comput Graph 16:1515-24 |
| Xu, Wei; Xu, Fang; Jones, Mel et al. (2010) High-performance iterative electron tomography reconstruction with long-object compensation using graphics processing units (GPUs). J Struct Biol 171:142-53 |
| Li, Shengying; Jackowski, Marcel; Dione, Donald P et al. (2010) Refraction corrected transmission ultrasound computed tomography for application in breast imaging. Med Phys 37:2233-46 |
| Xu, Fang; Xu, Wei; Jones, Mel et al. (2010) On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs. Comput Methods Programs Biomed 98:261-70 |
| Li, Shengying; Mueller, Klaus; Jackowski, Marcel et al. (2008) Physical-space refraction-corrected transmission ultrasound computed tomography made computationally practical. Med Image Comput Comput Assist Interv 11:280-8 |
| Wang, Lujin; Giesen, Joachim; McDonnell, Kevin T et al. (2008) Color design for illustrative visualization. IEEE Trans Vis Comput Graph 14:1739-46 |
| Giesen, Joachim; Mueller, Klaus; Schuberth, Eva et al. (2007) Conjoint analysis to measure the perceived quality in volume rendering. IEEE Trans Vis Comput Graph 13:1664-71 |
| Qiu, Feng; Xu, Fang; Fan, Zhe et al. (2007) Lattice-based volumetric global illumination. IEEE Trans Vis Comput Graph 13:1576-83 |
| Xu, Fang; Mueller, Klaus (2007) Real-time 3D computed tomographic reconstruction using commodity graphics hardware. Phys Med Biol 52:3405-19 |
