Revolutionizing Medical Imaging With Advanced CT Reconstruction
*Corresponding Author: Dr. Pavel Smirnov, Department of CT Imaging, Kyiv Medical University, Ukraine, Email: p.smirnov@ctrad.uaReceived Date: Aug 05, 2025 / Published Date: Aug 29, 2025
Citation: Smirnov DP (2025) Revolutionizing Medical Imaging With Advanced CT Reconstruction. J Radiol 14: 715.DOI: 10.4172/2167-7964.1000715
Copyright: © 2025 Dr. Pavel Smirnov This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited
Abstract
This document details advancements in computed tomography (CT) reconstruction algorithms. Key developments include modelbased iterative reconstruction (MBIR), deep learning-based reconstruction, and dual-energy CT (DECT) with advanced techniques. These methods significantly improve image quality, reduce radiation dose, and enhance diagnostic capabilities. Innovations like penalized maximum-likelihood (PML), adaptive statistical iterative reconstruction (ASIR), and artificial intelligence (AI) further refine imaging. The focus is on improved noise reduction, artifact suppression, spatial resolution, and quantitative accuracy, benefiting diverse clinical applications.
