Conventional reconstruction techniques, such as filtered back projection (FBP) and iterative
reconstruction (IR), which have been utilised widely in the image reconstruction process of …

Commercial iterative reconstruction techniques help to reduce the radiation dose of
computed tomography (CT), but altered image appearance and artefacts can limit their …

Purpose Deep learning‐based image denoising and reconstruction methods demonstrated
promising performance on low‐dose CT imaging in recent years. However, most existing …

Computed Tomography (CT) is a widely use medical image modality in clinical medicine,
because it produces excellent visualizations of fine structural details of the human body. In …

Deep learning (DL), part of a broader family of machine learning methods, is based on
learning data representations rather than task-specific algorithms. Deep learning can be …

There have been substantial advances in computed tomography (CT) technology since its
introduction in the 1970s. More recently, these advances have focused on image …

Abstract Purpose of Review Deep Learning reconstruction (DLR) is the current state-of-the-
art method for CT image formation. Comparisons to existing filter back-projection, iterative …

Low-dose CT (LDCT) imaging is preferred in many applications to reduce the object's
exposure to X-ray radiation. In recent years, one promising approach to image …

Purpose Deep neural network‐based image reconstruction has demonstrated promising
performance in medical imaging for undersampled and low‐dose scenarios. However, it …

Innovations in CT have been impressive among imaging and medical technologies in both
the hardware and software domain. The range and speed of CT scanning improved from the …