The reconstruction from sparse-view projections is one of important problems in computed tomography limited by the availability or feasibility of a large number of projections. Total variation (TV) approaches have been introduced to improve the reconstruction quality by smoothing the variation between ...
We present a flexible framework for robust computed tomog-raphy (CT) reconstruction with a specific emphasis on recovering thin 1D and 2D manifolds embedded in 3D volumes. To reconstruct such structures at resolutions below the Nyquist limit of the CT image sensor, we devise a new 3D structure...
Sparse-view x-ray CT reconstruction via total generalized variation regularization Sparse-view CT reconstruction algorithms via total variation (TV) optimize the data iteratively on the basis of a noise- and artifact-reducing model, resul... S Niu,Y Gao,Z Bian,... - 《Physics in Medicine & ...
Sparse-view imaging is a promising scanning approach which has fast scanning rate and low-radiation dose in X-ray computed tomography (CT). Conventional L1-norm based total variation (TV) has been widely used in image reconstruction since the advent of compressive sensing theory. However, with ...
2023 三维重建方向论文总结【上】【1】SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction(SparseFusion:用于三维重建的提取视图条 - 计算机sci 论文咨询于20240228发布在抖音,已经收获了1个喜欢,来抖音,记录美好生活!
Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with both accelerated scan and reduced projection/back-projection calculation. Despite the rapid developments, image noise and artifacts still remain a major issue in the low dose protocol. In this paper, a deep learn...
摘要: Two practical algorithms for limited-projection-view CT reconstruction are proposed.Reconstruction parameters of both algorithms are determined automatically.Computationally intense ART are saved if the data fidelity constraint is satisfied.关键词: Computed tomography Iterative reconstruction Total variation...
To train the sparse-view reconstruction models, please run: #Training on NeRF representationpython train.py --base configs/instant-nerf-large-train.yaml --gpus 0,1,2,3,4,5,6,7 --num_nodes 1#Training on Mesh representationpython train.py --base configs/instant-mesh-large-train.yaml --gp...
X-ray computed laminography is widely used in nondestructive testing of relatively flat objects using an oblique scanning configuration for data acquisition. In this work, a new scanning scheme is proposed in conjunction with the compressive-sensing-based image reconstruction for reducing imaging radiati...
In this study, we focused on CT image reconstruction from sparse-view or limited-angle projection data. Many iterative algorithms have been used for CT image reconstruction, and the actual iterative algorithms are well established12. Among them, statistical iterative reconstruction (SIR), which is ...