naa a22 4500 51080828X CHVBK 20180411083428.0 cr unu---uuuuu 180411e20130301xx s 000 0 eng 10.1007/s11548-012-0783-5 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0783-5 Fast reconstructed radiographs from octree-compressed volumetric data [Elektronische Daten] [Mark Fisher, Osama Dorgham, Stephen Laycock] Purpose: Simulated 2D X-ray images called digitally reconstructed radiographs (DRRs) have important applications within medical image registration frameworks where they are compared with reference X-rays or used in implementations of digital tomosynthesis (DTS). However, rendering DRRs from a CT volume is computationally demanding and relatively slow using the conventional ray-casting algorithm. Image-guided radiation therapy systems using DTS to verify target location require a large number DRRs to be precomputed since there is insufficient time within the automatic image registration procedure to generate DRRs and search for an optimal pose. Method: DRRs were rendered from octree-compressed CT data. Previous work showed that octree-compressed volumes rendered by conventional ray casting deliver a registration with acceptable clinical accuracy, but efficiently rendering the irregular grid of an octree data structure is a challenge for conventional ray casting. We address this by using vertex and fragment shaders of modern graphics processing units (GPUs) to directly project internal spaces of the octree, represented by textured particle sprites, onto the view plane. The texture is procedurally generated and depends on the CT pose. Results: The performance of this new algorithm was found to be 4 times faster than that of a ray-casting algorithm implemented using NVIDIA™Compute Unified Device Architecture (CUDA™) on an equivalent GPU (~95% octree compression). Rendering artifacts are apparent (consistent with other splatting algorithm), but image quality tends to improve with compression and fewer particles are needed. A peak signal-to-noise ratio analysis confirmed that the images rendered from compressed volumes were of marginally better quality to those rendered using Gaussian footprints. Conclusions: Using octree-encoded DRRs within a 2D/3D registration framework indicated the approach may be useful in accelerating automatic image registration. CARS, 2012 Digitally reconstructed radiographs nationallicence GPU acceleration nationallicence Direct rendering nationallicence 2D/3D image registration nationallicence Fisher Mark School of Computing Sciences, University of East Anglia, NR4 7TJ, Norwich, UK aut Dorgham Osama Prince Abdullah Bin Ghazzi Faculty of Information Technology, Al-Balqu Applied University, Amman, Jordan aut Laycock Stephen School of Computing Sciences, University of East Anglia, NR4 7TJ, Norwich, UK aut International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/2(2013-03-01), 313-322 1861-6410 8:2<313 2013 8 11548 https://doi.org/10.1007/s11548-012-0783-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0783-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Fisher Mark School of Computing Sciences, University of East Anglia, NR4 7TJ, Norwich, UK aut NATIONALLICENCE 700 1- Dorgham Osama Prince Abdullah Bin Ghazzi Faculty of Information Technology, Al-Balqu Applied University, Amman, Jordan aut NATIONALLICENCE 700 1- Laycock Stephen School of Computing Sciences, University of East Anglia, NR4 7TJ, Norwich, UK aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/2(2013-03-01), 313-322 1861-6410 8:2<313 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer