no code implementations • 24 Aug 2023 • Shaoyan Pan, Elham Abouei, Junbo Peng, Joshua Qian, Jacob F Wynne, Tonghe Wang, Chih-Wei Chang, Justin Roper, Jonathon A Nye, Hui Mao, Xiaofeng Yang
One of the most important tradeoffs in PET imaging is between image quality and radiation dose: high image quality comes with high radiation exposure.
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.
1 code implementation • Physics in Medicine & Biology 2023 • Shaoyan Pan, Tonghe Wang, Richard L J Qiu, Marian Axente, Chih-Wei Chang, Junbo Peng, Ashish B Patel, Joseph Shelton, Sagar A Patel, Justin Roper
In this paper, we introduce a medical image synthesis framework aimed at addressing the challenge of limited training datasets for AI models.
no code implementations • 28 Apr 2023 • Shaoyan Pan, Chih-Wei Chang, Junbo Peng, Jiahan Zhang, Richard L. J. Qiu, Tonghe Wang, Justin Roper, Tian Liu, Hui Mao, Xiaofeng Yang
The two DDPMs exchange random latent noise in the reverse processes, which helps to regularize both DDPMs and generate matching images in two modalities.
no code implementations • 25 Feb 2023 • Shaoyan Pan, Shao-Yuan Lo, Min Huang, Chaoqiong Ma, Jacob Wynne, Tonghe Wang, Tian Liu, Xiaofeng Yang
In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the delineation of Organs-At-Risk (OAR) in abdominal Computed Tomography (CT) to facilitate radiation therapy.
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.
no code implementations • 25 Mar 2021 • Mingquan Lin, Jacob Wynne, Yang Lei, Tonghe Wang, Walter J. Curran, Tian Liu, Xiaofeng Yang
We summarize the latest AI-based methods for tumor subregion analysis and their applications.
no code implementations • 8 Oct 2020 • Xianjin Dai, Yang Lei, Tonghe Wang, Anees H. Dhabaan, Mark McDonald, Jonathan J. Beitler, Walter J. Curran, Jun Zhou, Tian Liu, Xiaofeng Yang
The proposed method was evaluated on a cohort of 65 HN cancer patients.
Medical Physics Image and Video Processing
no code implementations • 28 Jan 2020 • Yang Lei, Yabo Fu, Tonghe Wang, Richard L. J. Qiu, Walter J. Curran, Tian Liu, Xiaofeng Yang
This paper presents a review of deep learning (DL) in multi-organ segmentation.
no code implementations • 18 Jan 2020 • Tonghe Wang, Yang Lei, Yabo Fu, Walter J. Curran, Tian Liu, Xiaofeng Yang
This paper reviewed the machine learning-based studies for quantitative positron emission tomography (PET).
no code implementations • 27 Dec 2019 • Yabo Fu, Yang Lei, Tonghe Wang, Walter J. Curran, Tian Liu, Xiaofeng Yang
Lastly, we analyzed the statistics of all the cited works from various aspects, revealing the popularity and future trend of development in medical image registration using deep learning.