Developing the Digital Lung

Developing the Digital Lung

From First Lung CT to Clinical AI

1st Edition - September 13, 2022

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  • Author: John Newell
  • eBook ISBN: 9780323795029
  • Paperback ISBN: 9780323795012

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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.

Table of Contents

  • 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

Product details

  • No. of pages: 160
  • Language: English
  • Copyright: © Elsevier 2023
  • Published: September 13, 2022
  • Imprint: Elsevier
  • eBook ISBN: 9780323795029
  • Paperback ISBN: 9780323795012

About the Author

John Newell

Dr. John Newell Jr, MD is a professor of Radiology and Biomedical Engineering, Director of the Radiology Image Phenotyping Laboratory and co-Director of the Iowa Institute for Biomedical Imaging. He has over 30 years of experience in clinical research and clinical practice in the Radiology sub-specialty of Cardio-Thoracic Radiology.): Dr. John Newell Jr, MD is a professor of Radiology and Biomedical Engineering, Director of the Radiology Image Phenotyping Laboratory and co-Director of the Iowa Institute for Biomedical Imaging. He has over 30 years of experience in clinical research and clinical practice in the Radiology sub-specialty of Cardio-Thoracic Radiology.

Affiliations and Expertise

University of Colorado, Health Sciences Center, Denver, CO, USA

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