no code implementations • 1 Feb 2023 • Tao Ge, Maria Medrano, Rui Liao, David G. Politte, Jeffrey F. Williamson, Bruce R. Whiting, Joseph A. O'Sullivan
Therefore, to improve its convergence, we have embedded DECT SIR into a deep learning model-based unrolled network for 3D DECT reconstruction (MB-DECTNet) that can be trained in an end-to-end fashion.
no code implementations • 31 Jan 2022 • Tao Ge, Maria Medrano, Rui Liao, Jeffrey F. Williamson, David G. Politte, Bruce R. Whiting, Joseph A. O'Sullivan
We compared DEAM with the proposed method to the original DEAM and vendor reconstructions with and without metal-artifact reduction for orthopedic implants (O-MAR).
no code implementations • 30 Jul 2021 • Tao Ge, Maria Medrano, Rui Liao, David G. Politte, Jeffrey F. Williamson, Joseph A. O'Sullivan
Dual-energy CT (DECT) has been widely investigated to generate more informative and more accurate images in the past decades.
no code implementations • 22 Mar 2019 • Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, Ali Kamen
The proposed registration approach is then built on the factorized latent shape code, with the assumption that the intrinsic shape deformation existing in original image domain is preserved in this latent space.
no code implementations • 11 Jun 2018 • Yue Zhang, Shun Miao, Tommaso Mansi, Rui Liao
In this paper, we propose a novel model framework for learning automatic X-ray image parsing from labeled CT scans.
no code implementations • 22 Nov 2017 • Shun Miao, Sebastien Piat, Peter Fischer, Ahmet Tuysuzoglu, Philip Mewes, Tommaso Mansi, Rui Liao
Second, to handle various artifacts in 2D X-ray images, multiple local agents are employed efficiently via FCN-based structures, and an auto attention mechanism is proposed to favor the proposals from regions with more reliable visual cues.
1 code implementation • 30 Nov 2016 • Rui Liao, Shun Miao, Pierre de Tournemire, Sasa Grbic, Ali Kamen, Tommaso Mansi, Dorin Comaniciu
The resulting registration approach inherently encodes both a data-driven matching metric and an optimal registration strategy (policy).
no code implementations • 27 Jul 2015 • Shun Miao, Z. Jane Wang, Rui Liao
In this paper, we present a Convolutional Neural Network (CNN) regression approach for real-time 2-D/3-D registration.