no code implementations • 3 Dec 2024 • Li Zhou, Changsheng Fang, Bahareh Morovati, Yongtong Liu, Shuo Han, Yongshun Xu, Hengyong Yu
This paper introduces $\rho$-NeRF, a self-supervised approach that sets a new standard in novel view synthesis (NVS) and computed tomography (CT) reconstruction by modeling a continuous volumetric radiance field enriched with physics-based attenuation priors.
no code implementations • 23 May 2024 • Shuo Han, Yongshun Xu, Dayang Wang, Bahareh Morovati, Li Zhou, Jonathan S. Maltz, Ge Wang, Hengyong Yu
Cardiac computed tomography (CT) has emerged as a major imaging modality for the diagnosis and monitoring of cardiovascular diseases.
no code implementations • 19 Mar 2024 • Mengzhou Li, Chuang Niu, Ge Wang, Maya R Amma, Krishna M Chapagain, Stefan Gabrielson, Andrew Li, Kevin Jonker, Niels de Ruiter, Jennifer A Clark, Phil Butler, Anthony Butler, Hengyong Yu
Despite the success of deep learning methods for 2D few-view reconstruction, applying them to HR volumetric reconstruction of extremity scans for clinical diagnosis has been limited due to GPU memory constraints, training data scarcity, and domain gap issues.
no code implementations • 19 Oct 2023 • Dayang Wang, Yongshun Xu, Shuo Han, Zhan Wu, Li Zhou, Bahareh Morovati, Hengyong Yu
Recently, transformer models emerged as a promising avenue to enhance LDCT image quality.
1 code implementation • 16 Aug 2023 • Zirong Li, Yanyang Wang, Jianjia Zhang, Weiwen Wu, Hengyong Yu
Score-based models have proven to be effective in addressing different inverse problems encountered in CT and MRI, such as sparse-view CT and fast MRI reconstruction.
no code implementations • 10 Oct 2022 • Dayang Wang, Yongshun Xu, Shuo Han, Hengyong Yu
A plethora of transformer models have been developed recently to improve LDCT image quality.
no code implementations • 3 Oct 2022 • Xiaodong Guo, Longhui Li, Dingyue Chang, Peng He, Peng Feng, Hengyong Yu, Weiwen Wu
Spectral computed tomography based on a photon-counting detector (PCD) attracts more and more attentions since it has the capability to provide more accurate identification and quantitative analysis for biomedical materials.
no code implementations • 16 Sep 2022 • Dayang Wang, Boce Zhang, Yongshun Xu, Yaguang Luo, Hengyong Yu
To the best of our knowledge, it is the first-of-its-kind on deep learning for lettuce browning prediction using a pretrained Siamese Quadratic Swin (SQ-Swin) transformer with several highlights.
2 code implementations • 28 Feb 2022 • Dayang Wang, Fenglei Fan, Zhan Wu, Rui Liu, Fei Wang, Hengyong Yu
Furthermore, an overlapped inference mechanism is introduced to effectively eliminate the boundary artifacts that are common for encoder-decoder-based denoising models.
2 code implementations • 14 Jan 2022 • Dayang Wang, Feng-Lei Fan, Bo-Jian Hou, Hao Zhang, Zhen Jia, Boce Zhou, Rongjie Lai, Hengyong Yu, Fei Wang
A neural network with the widely-used ReLU activation has been shown to partition the sample space into many convex polytopes for prediction.
no code implementations • 17 Jun 2021 • Weiwen Wu, Chuang Niu, Shadi Ebrahimian, Hengyong Yu, Mannu Kalra, Ge Wang
By the ALARA (As Low As Reasonably Achievable) principle, ultra-low-dose CT reconstruction is a holy grail to minimize cancer risks and genetic damages, especially for children.
2 code implementations • 8 Jun 2021 • Dayang Wang, Zhan Wu, Hengyong Yu
The model is free of convolution blocks and consists of a symmetric encoder-decoder block with sole transformer.
no code implementations • 4 Aug 2020 • Weiwen Wu, Dianlin Hu, Wenxiang Cong, Hongming Shan, Shao-Yu Wang, Chuang Niu, Pingkun Yan, Hengyong Yu, Varut Vardhanabhuti, Ge Wang
ACID synergizes a deep reconstruction network trained on big data, kernel awareness from CS-inspired processing, and iterative refinement to minimize the data residual relative to real measurement.
no code implementations • 17 Jul 2020 • Shilong Wang, Hang Liu, Anil Gaihre, Hengyong Yu
LDA is a statistical approach for topic modeling with a wide range of applications.
no code implementations • 30 May 2020 • Haimiao Zhang, Baodong Liu, Hengyong Yu, Bin Dong
Other components, such as image priors and hyperparameters, are kept as the original design.
no code implementations • 6 May 2019 • Weiwen Wu, Haijun Yu, Peijun Chen, Fulin Luo, Fenglin Liu, Qian Wang, Yining Zhu, Yanbo Zhang, Jian Feng, Hengyong Yu
Second, we employ the direct inversion (DI) method to obtain initial material decomposition results, and a set of image patches are extracted from the mode-1 unfolding of normalized material image tensor to train a united dictionary by the K-SVD technique.
1 code implementation • 22 Nov 2018 • Fenglei Fan, Dayang Wang, Hengtao Guo, Qikui Zhu, Pingkun Yan, Ge Wang, Hengyong Yu
In this paper, we investigate the expressivity and generalizability of a novel sparse shortcut topology.
no code implementations • 22 Oct 2018 • Weiwen Wu, Qian Wang, Fenglin Liu, Yining Zhu, Hengyong Yu
Spectral computed tomography (CT) has a great potential in material identification and decomposition.
no code implementations • 24 Jul 2018 • Weiwen Wu, Fenglin Liu, Yanbo Zhang, Qian Wang, Hengyong Yu
Then, as a new regularizer, Kronecker-Basis-Representation (KBR) tensor factorization is employed into a basic spectral CT reconstruction model to enhance the ability of extracting image features and protecting spatial edges, generating the non-local low-rank cube-based tensor factorization (NLCTF) method.
no code implementations • 13 Dec 2017 • Weiwen Wu, Yanbo Zhang, Qian Wang, Fenglin Liu, Peijun Chen, Hengyong Yu
The L0TDL method inherits the advantages of tensor dictionary learning (TDL) by employing the similarity of spectral CT images.
9 code implementations • 3 Aug 2017 • Qingsong Yang, Pingkun Yan, Yanbo Zhang, Hengyong Yu, Yongyi Shi, Xuanqin Mou, Mannudeep K. Kalra, Ge Wang
In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity.
no code implementations • 21 Nov 2016 • He Yang, Hengyong Yu, Ge Wang
Deep learning, as a promising new area of machine learning, has attracted a rapidly increasing attention in the field of medical imaging.
no code implementations • 22 Nov 2013 • Baodong Liu, Hengyong Yu, Scott S. Verbridge, Lizhi Sun, Ge Wang
In this paper, we evaluate the EST, ADSIR and an ordered-subset simultaneous algebraic reconstruction technique (OS-SART), and compare the ES and equally angled (EA) data acquisition modes.