… With such an implementation, we can see the performance of the NLM algorithm for low-dose
CT image restoration and also observe the gain obtained by the use of the previous normal…

… the need for better image quality in LDCT imaging, this paper … deeplearning-based image
reconstruction methods, as well … an image reconstruction method in LDCT whose image prior …

… such a prior image is not available, these methods could not be used. We propose a new
method for low dose CT reconstructions that combines conventional PWLS reconstruction with …

… In this paper, we describe an autoencoder-RegNet based framework for the low-dose CT
image reconstruction and compare it to baseline algorithms. The experimental results …

Objective: Deep learning image reconstruction (DLIR) is a new reconstruction method for
maintaining image quality at reduced radiation dose. The purpose of this study was to compare …

… ) of the images. This section first reviews some of the statistical models for CT measurements
along … about images for LDCT image reconstruction, and then presents our contributions. …

… to many other image types and various … image processing and reconstruction, and
explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose …

… low-dose CT reconstruction techniques on well-known benchmark low-dose CT images. …
2 demonstrates the use of dictionary learning for low-dose CT image reconstruction. Section 3 …

… Clearly, it is now time for CT vendors to open their data format, perform machine learning
and develop the next generation of CT image reconstruction algorithms in the DL framework. …

… CT [38], and abdomen LDCT image processing [39]. It has been widely accepted that the TV
based reconstruction can … in LDCT image processing, the general DL based processing is …