no code implementations • 4 May 2024 • Yang Lei, Luke A. Matkovic, Justin Roper, Tonghe Wang, Jun Zhou, Beth Ghavidel, Mark McDonald, Pretesh Patel, Xiaofeng Yang
By using topology-preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation.
1 code implementation • 31 May 2023 • Shaoyan Pan, Elham Abouei, Jacob Wynne, Tonghe Wang, Richard L. J. Qiu, Yuheng Li, Chih-Wei Chang, Junbo Peng, Justin Roper, Pretesh Patel, David S. Yu, Hui Mao, Xiaofeng Yang
The proposed model consists of two processes: a forward process which adds Gaussian noise to real CT scans, and a reverse process in which a shifted-window transformer V-net (Swin-Vnet) denoises the noisy CT scans conditioned on the MRI from the same patient to produce noise-free CT scans.
no code implementations • 14 Sep 2022 • Yupei Zhang, Xianjin Dai, Zhen Tian, Yang Lei, Jacob F. Wynne, Pretesh Patel, Yue Chen, Tian Liu, Xiaofeng Yang
We further tested the proposed model on 69 landmarks from the testing dataset that has a similar image pattern to the training pattern, resulting in a mean tracking error of 0. 94+/-0. 83 mm.
no code implementations • 29 Aug 2022 • Huiqiao Xie, Yang Lei, Yabo Fu, Tonghe Wang, Justin Roper, Jeffrey D. Bradley, Pretesh Patel, Tian Liu, Xiaofeng Yang
The STN consists of a global generative adversarial network (GlobalGAN) and a local GAN (LocalGAN) to predict the coarse- and fine-scale motions, respectively.