Fundamentals and Methods of Machine and Deep Learning

15Application of Deep Learning Algorithms in Medical Image Processing: A Survey

Santhi B.*, Swetha A.M. and Ashutosh A.M.

SASTRA Deemed University, Thanjavur, Tamil Nadu, India

Abstract

Deep learning (DL) in medical image processing (MIP) and segmentation for a long time and it continues to be the most popular and not to mention a powerful technique, given its exceptional capability in image processing and classification. From fledgeling DL models like convolutional neural networks (CNNs), which is, by far, the best rudimentary yet convoluted model for image classification, to complex algorithms like transfer learning which involves model construction on top of state-of-the-art pre-trained classifiers, DL has established itself as a capable and potential technique for medical imaging processing. Prior to the development of DL models, MIP or image processing, in general, was restricted to edge-detection filters and other automated techniques. But the advent of artificial intelligence (AI) and, along with it, the instances of ML and DL algorithms changed the facet of medical imaging. With adequate dataset and proper training, DL models can be made to perfect the task of analyzing medical images and detecting tissue damage or any equivalent tissue-related abnormality with higher precision.

This paper summarizes the evolution and contribution of various DL models in MIP over the past 5 years. This study extracts the fundamental information to draw the attention of researchers, ...