Machine Learning Applications In Medical Image Processing

Abstract

The term “learning” relate to a broad range of processes that can be defined as “knowledge or skill acquired by instruction or study.” Psychologists study learning in both humans and animals, but in this chapter, the authors focused on learning in machines and how this process has evolved during the last 60 years and found important applications in medical image processing. The author discussed how computational models built to understand human learning have led to two main categories of machine learning: supervised learning and unsupervised learning. They also presented the concepts of deep learning and how it is beginning to play a vital role in medical image processing. To help researchers interested in applying machine learning to medical imaging data, they have provided information about different data formats and available resources to analyze these data. The chapter concludes with a discussion of how machine learning is expected to continue to play an important role in medical image processing and, combined with a doctor’s experience, will help improve medical outcomes.