Introduction to Medical Imaging Informatics

TL;DR

This paper introduces the fundamentals of medical imaging informatics, highlighting recent advances in machine learning and computer vision that enhance disease detection, diagnosis, and prognosis prediction.

Contribution

It provides a comprehensive overview of core concepts and recent technological advancements in medical imaging informatics for improved patient care.

Findings

Recent deep learning techniques enable new quantitative image markers

Machine learning improves disease prediction accuracy

Advancements enhance medical image management and interpretation

Abstract

Medical imaging informatics is a rapidly growing field that combines the principles of medical imaging and informatics to improve the acquisition, management, and interpretation of medical images. This chapter introduces the basic concepts of medical imaging informatics, including image processing, feature engineering, and machine learning. It also discusses the recent advancements in computer vision and deep learning technologies and how they are used to develop new quantitative image markers and prediction models for disease detection, diagnosis, and prognosis prediction. By covering the basic knowledge of medical imaging informatics, this chapter provides a foundation for understanding the role of informatics in medicine and its potential impact on patient care.