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Developing the Digital Lung, 1st Edition. From First Lung CT to Clinical AI

ISBN: 9780323795012
ISBN: 9780323795012
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Περιγραφή

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.
Key Features
  • 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.
Author Information
By John D. Newell, MD FACR, University of Colorado, Health Sciences Center, Denver, CO, USA

Περιεχόμενα

Cover image
Title page
Table of Contents
Any screen, Any time, Anywhere
Copyright
Dedication
Acknowledgments
Preface
Chapter 1. Introduction to Lung CT AI
Abstract
AI: An Intelligent Agent
Diagnosis of COPD, ILD, Lung Cancer, and Other Smoking-Related Diseases
Information for Healthcare Providers and Administrators, Patients, and Researchers
Describing Lung CT AI in Three Stages
References
Chapter 2. Three-Dimensional (3D) Digital Images of the Lung Using X-ray Computed Tomography
Abstract
The Digital Lung
X-ray Computed Tomography
CT Scanning Protocols
X-ray CT Radiation Dose
Brief History of X-ray CT
References
Chapter 3. X-ray CT Scanning Protocols for Lung CT AI Applications
Abstract
Early Work in the Development of QCT Scanning Protocols
Current Recommended Quantitative CT Scanning Protocol
CT Scanner Quality Control
Current QIBA Lung Density CT Profile
Summary
References
Chapter 4. Quantitative Assessment of Lung Nodule Size, Shape, and Malignant Potential Using Both Reactive and Limited-Memory Lung CT AI
Abstract
CT Assessment of Lung Nodules—CT Versus Projection Radiography (PR)
CT Determination of Lung Nodule Size
CT Determination of Nodule Growth
CT Determination of Nodule Density
CT Determined Nodule Mass, Location, Morphology, Shape, Contour
CT Determined Nodule Texture—Limited-Memory AI
CT Assessment of Lung Tissue Adjacent to the Lung Nodule—Limited-Memory AI
References
Chapter 5. Using Reactive Machine AI to Derive Quantitative Lung CT Metrics of COPD, ILD, and COVID-19 Pneumonia
Abstract
Introduction
Normal Lung Structure
QCT Scanning Protocol and Lung Segmentation
Chronic Obstructive Pulmonary Disease (COPD) Induced Changes in Lung Structure
Clinical Value of Using Lung CT AI in Patients with Environmental Exposure to Cigarette Smoke
Interstitial Lung Disease (ILD) Induced Changes in Lung Structure
QCT of COVID-19 Acute Viral Pneumonia
Summary
References
Chapter 6. Using Reactive Machine AI and Dynamic Changes in Lung Structure to Derive Functional Quantitative Lung CT Metrics of COPD, ILD, and Asthma
Abstract
Introduction
Expiratory QCT Assessment of Air Trapping Due to Small Airway Disease in the Lung
Assessment of Air Trapping at the Voxel Level Using Image Registration
Assessment of Biomechanics and Tissue Stiffness Using Image Registration
Direct Measurements of Large Airway Geometry Using Lung CT AI
Summary
References
Chapter 7. Using Limited Memory Lung CT AI to Derive Advanced Quantitative CT Lung Metrics of COPD, ILD, and COVID-19 Pneumonia
Abstract
Introduction
Limited Memory Lung CT AI and the Assessment of Emphysema
Limited Memory Lung CT AI and the Assessment of Interstitial Lung Disease (ILD)
CNN for COVID-19 Pneumonia
Summary
References
Chapter 8. Lung CT AI Enables Advanced Computer Modeling of Lung Physiome Structure and Function
Abstract
Virtual Physiological Human and a Lung Physiome Model
Finite Element Model of Lung Structure and Function
Lung Physiome (LP) Model Applied to the Assessment of Acute Pulmonary Embolism
Summary of Important Concepts of the Lung Physiome Model
References
Chapter 9. Adoption of Lung CT AI Into Clinical Medicine
Abstract
Introduction
Healthcare Imaging IT
Electronic Medical Record (EMR)
Clinical Lung CT AI Software
Responsible AI
References
Index
Confidence is ClinicalKey