A Big Wave of Deep Learning in Medical Imaging - Analysis of Theory and Applications

Abstract

Deep learning models have become the province of cutting-edge machine learning models that are widely used in medical imaging in multiple kinds of ranging from image recognition to natural language processing. This article presents a brief overview on the recent developments and some relevant issues in medical image processing and image analysis as they related to machine learning. The proposed article will not cover the entire application landscape because it is becoming a very large and rapidly growing field, but will instead focus primarily on deep learning theory and techniques in medical imaging. Our goal is threefold: (i) To provide such a brief overview to deep medical imaging learning; (ii) To represent different approaches as well as comparisons of how deep learning has been accomplished, from image retrieval to segmentation to disease prediction; (iii) Provide the current medical imaging-related deep learning applications.