Chapter 1 - Introduction to Lung CT AI

Abstract

This chapter introduces the concept of AI and the different levels of AI used in this book. The chapter describes the rationale for writing this book and the topics that will be covered. The book’s focus is the application of multiple AI agents to obtain and analyze noncontrast x-ray computed tomography (CT) images of the lung to detect and quantitatively assess lung disease. The book describes how best to generate high-quality CT images of the thorax, segment the lung from the rest of the thoracic anatomy, extract quantitative CT (QCT) features from the lung CT images that represent meaningful metrics of normal and diseased lung structure and function, and then to analyze these features to detect and assess lung disease. The book describes how the 3D anatomic information from x-ray CT images of the thorax can be used to build an advanced computer model of lung structure and function in the assessment of pulmonary emboli. The book also describes how lung CT AI can now be implemented in an efficient and effective way into the clinical medical imaging environment. Lung CT AI can use a number of lung CT AI metrics to detect and quantitatively assess different lung diseases in near realtime for patients and their health care providers.