Medical Images Analysis Using Deep Learning Technique

Abstract

Clinical picture classification, pattern recognition, and quantification have seen significant advancements with the help of artificial intelligence, particularly through deep learning techniques. Deep learning has rapidly emerged as the most rapidly evolving field within AI, and its applications have been successfully demonstrated across various domains, including medicine. This review briefly examines recent applied research in several medical fields, such as neurology, brain imaging, retinal analysis, pneumonics, computerized pathology, breast imaging, cardiovascular studies, musculoskeletal imaging, and gastrointestinal imaging. Deep learning networks prove to be highly effective when dealing with large-scale medical datasets, enabling information discovery, knowledge dissemination, and knowledge-based prediction. This research aims to present both foundational knowledge and state-of-the-art deep learning techniques to facilitate the interpretation and analysis of medical images. The primary objectives of this work are to explore advancements in medical image processing research and implement the identified and addressed key criteria in practical applications.