Sparse-view reconstruction Convolutional neural networksGenerative adversarial networks L1 lossWe propose a 2D computed tomography (CT) slice image reconstruction method from a limited number of projection images using Wasserstein generative adversarial networks (wGAN). Our wGAN optimizes the 2D CT image ...
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 CT reconstruction based on gradient directional total variation 下载积分: 750 内容提示: 1 © 2019 IOP Publishing Ltd Printed in the UK1. IntroductionLow-dose computed tomography (CT) image reconstruc-tion has been widely used in industrial CT and medical CT [1]. In the medical ...
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...
In the synchrotron radiation tomography experiment, sparse-view sampling is capable of reducing severe radiation damages of samples from X-ray, accelerating sampling rate and decreasing total volume of experimental dataset. Consequently, the sparse-view CT reconstruction has been a hot topic nowadays. ...
摘要: 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) ap关键词: Computed tomography Sparse-view reconstruction Curvelet Total variation ...
This has led to a growing interest in sparse-view CBCT reconstruction to reduce radiation doses. While recent advances, including deep learning and neural rendering algorithms, have made strides in this area, these methods either produce unsatisfactory results or suffer from time inefficiency of ...
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 ...
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 ...
c, Challenges in paired multi-view 2D X-ray angiography and 3D ground truth. Each dot in view time space represents an image at a unique pose and time, and a sequence forms a scanning pattern (Pattern I, red segments). For 3D reconstruction of blue-dot image, simultaneous multi-view ...