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Elsevier

Developing the Digital Lung

From First Lung CT to Clinical AI

  • 1 Edición - 13 de septiembre de 2022
  • Última edición
  • Autor: John D. Newell
  • Idioma: Inglés

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… Leer más

Descripción

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.

Puntos claves

  • 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.

Índice

1 Introduction to Lung CT AI

2 Three-Dimensional (3D) Digital Images of the Lung Using X-ray Computed Tomography

3 X-ray CT Scanning Protocols for Lung CT AI Applications

4 Quantitative Assessment of Lung Nodule Size, Shape, and Malignant Potential Using Both Reactive and Limited-Memory Lung CT AI

5 Using Reactive Machine AI to Derive Quantitative Lung CT Metrics of COPD, ILD, and COVID-19 Pneumonia

6 Using Reactive Machine AI and Dynamic Changes in Lung Structure to Derive Functional Quantitative Lung CT Metrics of COPD, ILD, and Asthma

7 Using Limited Memory Lung CT AI to Derive Advanced Quantitative CT Lung Metrics of COPD, ILD, and COVID-19 Pneumonia

8 Lung CT AI Enables Advanced Computer Modeling of Lung Physiome Structure and Function

9 Adoption of Lung CT AI Into Clinical Medicine
Index

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 16 de diciembre de 2022
  • Idioma: Inglés

Sobre el autor

JN

John D. Newell

Dr John D Newell Jr MD FACR is a Visiting Professor of Radiology and Biomedical Engineering at the University of Iowa and the Medical Advisor to VIDA, a lung CT AI software company. He has over 40 years of experience in CardioThoracic Radiology and Biomedical Engineering. He has been researching and publishing in the area of lung CT AI for many years and wants to help translate the research done in lung CT AI into the clinical care of patients with lung disease. He lives in Port Townsend, Washington.
Afiliaciones y experiencia
University of Colorado, Health Sciences Center, Denver, CO, USA

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