RECENT ADVANCES AND FUTURE PERSPECTIVES OF ARTIFICIAL INTELLIGENCE IN MEDICAL IMAGING: A REVIEW

Abstract

Radiology can benefit significantly from various new Artificial Intelligence (AI) tools. The application of machine learning algorithms and deep learning techniques help radiologists interpret medical images more accurately and efficiently and to lower radiographers' human errors is known as AI in radiology. The goal of this review article is to provide an overview of AI applications in radiology for precise diagnosis and treatment, optimizing workflow and image quality while reducing radiation dose. Articles published related to the study were searched and evaluated from indexed journals on PubMed, Springer, and Elsevier databases from January 2000 to December 2023. With automation and process optimization for data collecting, including patient positioning and acquisition parameter settings. To enhance various aspects of image quality, such as reducing image noise and utilising lower radiation doses for data collection, it is necessary to take steps such as collecting data, using advanced reconstruction algorithms, employing image denoising techniques, and optimising image reconstruction parameters. In this review article we concluded that AI enhances diagnosis and treatment planning; it has the potential to transform the medical imaging and healthcare sector completely. In this review, we discussed the current developments of AI in the field of medical imaging technology. We concluded that AI enhances diagnosis and treatment planning; it has the potential to transform the medical imaging and healthcare sector completely.