低剂量 CT 去噪
本主题下的论文、它们使用的数据集、聚焦该主题的团队、归入该主题的工具包，以及在此发表多篇论文的作者。点选任意节点查看它的连接。
交互图谱未能加载（JavaScript 或图谱库不可用）；下方以链接形式列出了同样的条目。
低剂量 CT 去噪
研究团队
- Bouman 课题组
- CT 临床创新中心
- Fessler 课题组
- UW CT 实验室
- WANG-AXIS 实验室 / 生物医学成像中心
- X 射线断层成像课题组
- 东南大学 CT 重建组（陈阳 / 罗守华）
- 剑桥大学计算图像分析组
- 瑞典皇家理工学院 Öktem 课题组
主题
论文
- 3D Helical CT Reconstruction With a Memory Efficient Learned Primal-Dual Architecture
- 3pADMM
- AdaIN-Based Tunable CycleGAN for Efficient Unsupervised Low-Dose CT Denoising
- AgenticCT
- AllFreqNet
- AMIR
- An Unsupervised Reconstruction Method For Low-Dose CT Using Deep Generative Regularization Prior
- Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: A review
- ASCON
- AWTV
- BCD-Net
- Ca-ResUnet
- CADL
- CCN-CL
- CLEAR
- CoCoDiff
- ContiLNN
- CoreDiff
- CPCE
- CTformer
- CTPretrain
- Cycle-Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography
- Cycle-Free CycleGAN Using Invertible Generator for Unsupervised Low-Dose CT Denoising
- CycleGAN denoising of extreme low-dose cardiac CT using wavelet-assisted noise disentanglement
- DADN
- DDN-FM
- DeACNN
- Dedicated convolutional neural network for noise reduction in ultra-high-resolution photon-counting detector computed tomography
- Deep Convolutional Neural Network for Inverse Problems in Imaging
- Deep learning CT image restoration using system blur and noise models
- Deep Learning-Based Dictionary Learning and Tomographic Image Reconstruction
- DenoMamba
- DESDGAN
- DFDLM
- DiffCode
- Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising
- DIRE
- Dose-Aware Cold Diffusion with Physics Consistency for Generalizable Low-Dose CT Reconstruction
- DP-ResNet
- DPER
- DU-GAN
- Dual-AGNet
- DuDoUFNet
- EAGLE
- EASEL
- EDCNN
- End-to-End Deep Learning for Interior Tomography with Low-Dose X-ray CT
- FedM2CT
- Filter2Noise
- FORCE
- Foundation-VAE
- FoundDiff
- Generative Adversarial Networks for Noise Reduction in Low-Dose CT
- GGMRF
- HARU-Net
- HounsWorld
- IMAP-TV
- IRDS
- K-SVD
- KSAE
- LangMamba
- Learned denoising with simulated and experimental low-dose CT data
- LEDA
- LoDoPaB-CT
- Low-dose cerebral perfusion computed tomography image restoration via low-rank and total variation regularizations
- Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20× Speedup
- Low-dose CT via convolutional neural network
- Low-Dose Dynamic Cerebral Perfusion Computed Tomography Reconstruction via Kronecker-Basis-Representation Tensor Sparsity Regularization
- Low-dose X-ray computed tomography image reconstruction with a combined low-mAs and sparse-view protocol
- Low-Dose X-ray CT Reconstruction via Dictionary Learning
- Low-dose x-ray tomography through a deep convolutional neural network
- Low-Level Dataset Distillation for Medical Image Enhancement
- MAGIC
- MALAR
- MAP-NN
- MBDL
- MSM/TomoTx
- Multislice input for 2D and 3D residual convolutional neural network noise reduction in CT
- MVSS-PCR
- N2S
- Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstruction
- Noise2Inverse
- Noise2Match
- PALETTE
- PDuMSRNet
- Performance of a deep learning-based CT image denoising method: Generalizability over dose, reconstruction kernel, and slice thickness
- PnP
- Preserving noise texture through training data curation for deep learning denoising of high-resolution cardiac EID-CT
- PWLS-ULTRA
- RDDM
- RED
- RED-CNN
- REDAEP
- SACNN
- SAGAN
- SDF
- SENP
- SinoNet
- Slice-wise reconstruction for low-dose cone-beam CT using a deep residual convolutional neural network
- SMGAN
- Spatial resolution properties of penalized-likelihood image reconstruction: space-invariant tomographs
- SPULTRA
- SSDA
- ST_CNN
- Statistical Image Reconstruction Using Mixed Poisson-Gaussian Noise Model for X-Ray CT
- SUPER-2
- Synergizing Physics/Model-based and Data-driven Methods for Low-Dose CT
- TAMP
- TAT
- Technical note: Phantom-based training framework for convolutional neural network CT noise reduction
- TMGAN
- To recurse or not to recurse: a low-dose CT study
- TOD-Net
- TomoGAN
- Toward CT-Equivalent Image Quality in Low-Dose Radiotherapy Planning: Conditional Diffusion-Based CBCT-to-CT Synthesis and the Impact of CBCT Input Representation
- Trainable joint bilateral filters for enhanced prediction stability in low-dose CT
- TransCT
- Ultra-High-Resolution Photon-Counting-Detector CT with a Dedicated Denoising Convolutional Neural Network for Enhanced Temporal Bone Imaging
- Ultralow-parameter denoising: Trainable bilateral filter layers in computed tomography
- UniMedIR
- UniSino
- VVBP-tSVD
- WavResNet
- WGAN-VGG
- Zero-Shot Low-dose CT Denoising via Sinogram Flicking
- ZIRCON
工具包
数据集
基准
作者
- Akitoshi Inoue
- Andreas Maier
- Andrew D. Missert
- Bingzheng Wei
- Charles A. Bouman
- Chenyu You
- Chuang Niu
- Cynthia H. McCollough
- Deyu Meng
- Dianlin Hu
- Dong Liang
- Dong Zeng
- Doğa Gürsoy
- Dufan Wu
- Emily K. Koons
- Fabian Wagner
- Fenglei Fan
- Francesco De Carlo
- Ge Wang
- Georges El Fakhri
- Guotao Quan
- Hao Zhang
- Hengyong Yu
- Hongkai Yang
- Hongming Shan
- Hu Chen
- Hua Zhang
- Huazhong Shu
- Huidong Xie
- Jamison E. Thorne
- Jawook Gu
- Jean-Louis Coatrieux
- Jeffrey A. Fessler
- Jianhua Ma
- Jiliu Zhou
- Jin Liu
- Jing Huang
- Jiping Wang
- Joel G. Fletcher
- Jong Chul Ye
- Junping Zhang
- K. Joost Batenburg
- Kaichao Liang
- Kyungsang Kim
- Li Zhang
- Lifeng Yu
- Limin Luo
- Linda-Sophie Schneider
- Mannudeep K. Kalra
- Mareike Thies
- Mingxuan Gu
- Nathan R. Huber
- Ozan Öktem
- Peixi Liao
- Pingkun Yan
- Qi Gao
- Qi Gao
- Qi Xie
- Qianlong Zhao
- Qiaoqiao Ding
- Qiegen Liu
- Quanzheng Li
- Saiprasad Ravishankar
- Shanli Zhang
- Shanzhou Niu
- Shaojie Chang
- Shuai Leng
- Siming Bayer
- Siqi Ye
- Siyuan Mei
- Weiwen Wu
- Wenjun Xia
- Wufan Chen
- Xiaokun Liang
- Xiaoqun Zhang
- Xuanqin Mou
- Yan Lei Xu
- Yan Liu
- Yang Chen
- Yi Zhang
- Yikun Zhang
- Yixing Huang
- Yong Qiang Long
- Yongbo Wang
- Yongqiang Huang
- Yongyi Shi
- Yuxiang Xing
- Z. P. Chen
- Zhanli Hu
- Zhaoying Bian
- Zhengrong Liang
- Zhiqiang Chen
- Zhiwen Yang
- Zhongxing Zhou
- Zongben Xu