Main description:

Reflecting recent major advances in the field of artificial intelligence, Developing the Digital Lung, From First Lung CT to Clinical AI, by Dr. John Newell, is your go-to reference for all aspects of applied artificial intelligence in lung disease development, including application to clinical medicine. It provides a unique overview of the field, beginning with a review of the origins of artificial intelligence in the mid-1970s and progressing to its application to clinical medicine in the early 2020s. Organized based on the four stages of development, this practical, easy-to-use resource helps you effectively apply artificial intelligences to lung imaging.

Traces the development of precise quantitative CT of diffuse lung disease through the use of applied AI, leading to faster effective diagnosis of patients with lung disease.

Reviews CT manufacturers, models and scanning protocol used to produce the 3D digital maps of the lungs.

Discusses how the data processed by AI algorithms can produce measures of emphysema, air trapping, and airway wall thickening in subjects with COPD and measures of pulmonary fibrosis and traction bronchiectasis in idiopathic pulmonary fibrosis (IPF).

Demonstrates the differences between reactive machine AI and limited memory AI methods.

Includes comprehensive case studies and current information on cloud computing.

An eBook version is included with purchase. The eBook allows you to access all of the text, figures and references, with the ability to search, customize your content, make notes and highlights, and have content read aloud.

Contents:

Introduction

History of AI CT of the Lung

Lung CT Imaging Protocols and their role in enabling AICTL

Lung Segmentation, critical first step in AICTL

AI Lung Quantitative CT Metrics - Reactive Machine

AI Quantitative CT Metrics - Limited Memory Machine

How public and industry funded research drove AICTL

Adoption of AICTL into Clinical Radiology

Adoption of AICTL into Healthcare Enterprises

Future Directions