An Overview of Analysis of Medical Images Using Data Visualization and Deep Learning Applications

Abstract

Regarding the importance of the right diagnosis in medical applications, various methods have been exploited for processing medical images. Machine Learning (ML) techniques have shown their unique capabilities in the field of medical image processing and segmentation. In recent years, efforts have been made to develop more accurate and efficient ML methodology for segmenting medical and natural images. Various automatic segmentation tools exist, but deep learning (DL)-based methods have proven to be much more accurate in various medical image segmentation tasks in recent years. Recent decades have seen DL achieve unprecedented success across various domains, including images, text, and speech. It also has been successfully implemented in medical image classification using DL methodology. This work focuses on the important role of DL in medical image segmentation, classification, and recognition, which will inspire the further use of DL in the field of medical images analysis and diagnosis.