… This review will discuss applications of artificial intelligence (AI) within CT image
reconstruction. A history of CT image reconstruction techniques will be discussed in terms of its …

In this paper we describe an investigation into the application of deep learning methods for
low-dose and sparse angle computed tomography using small training datasets. To motivate …

… % overlap was reconstructed at 70 keV using 40% adaptive statistical iterative reconstruction–…
The DLIR algorithm used for image reconstruction in this study was a vendor-specific deep …

… Computed tomography (CT) scanners visualize internal … , CT or other tomographic imaging
modalities, the measurements … -interpretable images are formed. The process of computing …

… maintaining image quality. The purposes of this study was to … image quality and noise of
LDCT scan images reconstructed with DLIR and compare with those of images reconstructed …

… In this paper, we propose a variational model for the limited-angle computed tomography
(CT) image reconstruction and convert it into an end-to-end deep network. We first use the …

… reconstruct a high-quality image for the limited-angle TCT scanning mode, we develop a
limited-angle TCT image reconstruction … we import the image reconstructed by SART method to …

… Multidetector computed tomography … image reconstruction algorithms that improve and
optimize data processing to allow for radiation dose reduction while maintaining diagnostic image …

… Background Computed tomography (CT) is a central modality in modern radiology
contributing to diagnostic medicine in almost every medical subspecialty, but particularly in …

… image quality, image noise, and conspicuity of PDAC on pancreatic LDCT images reconstructed
using DLIR and compares these parameters with those of images reconstructed using …