Fast calculation of digitally reconstructed radiographs using light fields

Daniel B. Russakoff; Torsten Rohlfing; Daniel Rueckert; Ramin Shahidi; Daniel Kim; Calvin R. Maurer Jr.

doi:10.1117/12.481888

15 May 2003 Fast calculation of digitally reconstructed radiographs using light fields

Daniel B. Russakoff, Torsten Rohlfing, Daniel Rueckert, Ramin Shahidi, Daniel Kim, Calvin R. Maurer Jr.

Author Affiliations +

Proceedings Volume 5032, Medical Imaging 2003: Image Processing; (2003) https://doi.org/10.1117/12.481888
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

Calculating digitally reconstructed radiographs (DRRs)is an important step in intensity-based fluoroscopy-to-CT image registration methods. Unfortunately, the standard techniques to generate DRRs involve ray casting and run in time O(n³),where we assume that n is approximately the size (in voxels) of one side of the DRR as well as one side of the CT volume. Because of this, generation of DRRs is typically the rate-limiting step in the execution time of intensity-based fluoroscopy-to-CT registration algorithms. We address this issue by extending light field rendering techniques from the computer graphics community to generate DRRs instead of conventional rendered images. Using light fields allows most of the computation to be performed in a preprocessing step;after this precomputation step, very accurate DRRs can be generated in time O(n²). Using a light field generated from 1,024 DRRs of resolution 256×256, we can create new DRRs that appear visually identical to ones generated by conventional ray casting. Importantly, the DRRs generated using the light field are computed over 300 times faster than DRRs generated using conventional ray casting(50 vs.17,000 ms on a PC with a 2 GHz Intel Pentium 4 processor).

Citation Download Citation

Daniel B. Russakoff, Torsten Rohlfing, Daniel Rueckert, Ramin Shahidi, Daniel Kim, and Calvin R. Maurer Jr. "Fast calculation of digitally reconstructed radiographs using light fields", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.481888

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