A Review: Low-Dose Computed Tomography Image Reconstruction Using Deep Learning Techniques

In Medical Healthcare System the Computed Tomography (CT) scan plays a vital role to generate the visualization of structural details of human body. In clinical procedure, the normal dose CT as well as high dose CT scan can produce high quality image than low dose CT scan, but the human body exposed to the Radiation. The low-dose CT scan can minimize the radiation, but it compromises the quality of image and it may not sufficient to make a decision by radiologist. So, the low-dose CT image has to undergo denoising and reconstruction phases to gain the quality of the image for right diagnosis. Image processing, Deep Learning (DL), and Machine Learning (ML) techniques are had been applied in a diversity of strategies. The aim of this investigation study is to conduct a systematic review of Deep Learning approaches to acquire reconstructions of low dose images in CT scans, identify their limitations, and suggest future research directions.