Computer Graphics
TU Braunschweig

Real-Time High-Resolution Cone-Beam CT Using GPU-Based Multi-Resolution Sampling


Real-Time High-Resolution Cone-Beam CT Using GPU-Based Multi-Resolution Sampling

We propose a GPU-based approach to accelerate filtered backprojection (FBP)-type computed tomography (CT) algorithms by adaptively reconstructing only relevant regions of the object at full resolution. In industrial applications, the object’s insensitivity to radiation as well as lack of inner motion allow for high-resolution scans. The large amounts of recorded data, however, pose serious challenges as the computational cost of CT reconstruction scales quartically with resolution. To ensure real-time reconstruction (i.e. faster processing than projection acquisition) for high-resolution scans, our method skips below-threshold voxels and monotonous regions inside the object.

Our approach is able to speed up the reconstruction process by a factor of up to 13 while simultaneously reducing memory requirements by a factor of up to 71.


Author(s):Markus Wedekind, Marc Kassubeck, Marcus Magnor
Published:to appear
Type:Article in conference proceedings
Book:Proc. IEEE International Conference on Image Processing (ICIP)
Presented at:IEEE International Conference on Image Processing (ICIP) 2018


@inproceedings{wedekind2018real-time,
  title = {Real-Time High-Resolution Cone-Beam {CT} Using {GPU}-Based Multi-Resolution Sampling},
  author = {Wedekind, Markus and Kassubeck, Marc and Magnor, Marcus},
  booktitle = {Proc. {IEEE} International Conference on Image Processing ({ICIP})},
  year = {2018}
}

Authors