US 11,806,175 B2
Few-view CT image reconstruction system
Huidong Xie, Troy, NY (US); Ge Wang, Loudonville, NY (US); Hongming Shan, Troy, NY (US); and Wenxiang Cong, Albany, NY (US)
Assigned to Rensselaer Polytechnic Institute, Troy, NY (US)
Appl. No. 17/642,725
Filed by Huidong Xie, Troy, NY (US); Ge Wang, Loudonville, NY (US); Hongming Shan, Troy, NY (US); and Wenxiang Cong, Albany, NY (US)
PCT Filed Sep. 14, 2020, PCT No. PCT/US2020/050654
§ 371(c)(1), (2) Date Mar. 14, 2022,
PCT Pub. No. WO2021/051049, PCT Pub. Date Mar. 18, 2021.
Claims priority of provisional application 62/899,517, filed on Sep. 12, 2019.
Claims priority of provisional application 63/077,745, filed on Sep. 14, 2020.
Prior Publication US 2022/0375142 A1, Nov. 24, 2022
Int. Cl. A61B 6/03 (2006.01); G06T 11/00 (2006.01); A61B 6/00 (2006.01)
CPC A61B 6/032 (2013.01) [A61B 6/5205 (2013.01); G06T 11/005 (2013.01); G06T 11/006 (2013.01); G06T 2211/421 (2013.01); G06T 2211/436 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A few-view computed tomography (CT) image reconstruction system, the system comprising:
a preprocessing module configured to apply a ramp filter to an input sinogram to yield a filtered sinogram;
a first generator network configured to receive the filtered sinogram, to learn a filtered back-projection operation and to provide a first reconstructed image as an output, the first reconstructed image corresponding to the input sinogram; and
a discriminator network configured to determine whether a received image corresponds to the first reconstructed image or a corresponding ground truth image, the first generator network and the discriminator network corresponding to a Wasserstein generative adversarial network (WGAN), the WGAN optimized using an objective function based, at least in part, on a Wasserstein distance and based, at least in part, on a gradient penalty.