Computed tomography and artificial intelligence

Damini Dey; Andrew Lin; Donghee Han; Piotr J. Slomka

doi:10.1016/B978-0-12-820273-9.00009-9

Computed tomography and artificial intelligence

Damini Dey
, Andrew Lin
, Donghee Han
, Piotr J. Slomka

Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Other › peer-review

3 Citations (Scopus)

Abstract

In the past 2decades, significant advances in computed tomography (CT) hardware and software have expanded the clinical utility of CT imaging. Hardware improvements include faster gantry rotation with improved temporal resolution, improved spatial resolution, and greater coverage of the patient, enabling faster acquisition. Concurrently, there have been applications of artificial intelligence (AI) in all aspects of CT imaging-acquisition, reconstruction, analysis, and measurement of novel image features-which may further improve the value and reduce cost. Chapter 9 summarizes the recent advances in AI applied to several key aspects of CT imaging, interpretation, and analysis.

Original language	English
Title of host publication	Machine Learning in Cardiovascular Medicine
Editors	Subhi J. Al'Aref, Gurpreet Singh, Lohendran Baskaran, Dimitris Metaxas
Place of Publication	London UK
Publisher	Elsevier
Chapter	9
Pages	211-239
Number of pages	29
ISBN (Electronic)	9780128202739
DOIs	https://doi.org/10.1016/B978-0-12-820273-9.00009-9
Publication status	Published - 2021
Externally published	Yes

Keywords

Artificial intelligence
Computed tomography
Deep learning
Diagnosis
Machine learning
Prognosis

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10.1016/B978-0-12-820273-9.00009-9

Cite this

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title = "Computed tomography and artificial intelligence",

abstract = "In the past 2decades, significant advances in computed tomography (CT) hardware and software have expanded the clinical utility of CT imaging. Hardware improvements include faster gantry rotation with improved temporal resolution, improved spatial resolution, and greater coverage of the patient, enabling faster acquisition. Concurrently, there have been applications of artificial intelligence (AI) in all aspects of CT imaging-acquisition, reconstruction, analysis, and measurement of novel image features-which may further improve the value and reduce cost. Chapter 9 summarizes the recent advances in AI applied to several key aspects of CT imaging, interpretation, and analysis.",

keywords = "Artificial intelligence, Computed tomography, Deep learning, Diagnosis, Machine learning, Prognosis",

author = "Damini Dey and Andrew Lin and Donghee Han and Slomka, \{Piotr J.\}",

year = "2021",

doi = "10.1016/B978-0-12-820273-9.00009-9",

language = "English",

pages = "211--239",

editor = "\{J. Al'Aref\}, Subhi and Gurpreet Singh and Lohendran Baskaran and Dimitris Metaxas",

booktitle = "Machine Learning in Cardiovascular Medicine",

publisher = "Elsevier",

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TY - CHAP

T1 - Computed tomography and artificial intelligence

AU - Dey, Damini

AU - Lin, Andrew

AU - Han, Donghee

AU - Slomka, Piotr J.

PY - 2021

Y1 - 2021

N2 - In the past 2decades, significant advances in computed tomography (CT) hardware and software have expanded the clinical utility of CT imaging. Hardware improvements include faster gantry rotation with improved temporal resolution, improved spatial resolution, and greater coverage of the patient, enabling faster acquisition. Concurrently, there have been applications of artificial intelligence (AI) in all aspects of CT imaging-acquisition, reconstruction, analysis, and measurement of novel image features-which may further improve the value and reduce cost. Chapter 9 summarizes the recent advances in AI applied to several key aspects of CT imaging, interpretation, and analysis.

AB - In the past 2decades, significant advances in computed tomography (CT) hardware and software have expanded the clinical utility of CT imaging. Hardware improvements include faster gantry rotation with improved temporal resolution, improved spatial resolution, and greater coverage of the patient, enabling faster acquisition. Concurrently, there have been applications of artificial intelligence (AI) in all aspects of CT imaging-acquisition, reconstruction, analysis, and measurement of novel image features-which may further improve the value and reduce cost. Chapter 9 summarizes the recent advances in AI applied to several key aspects of CT imaging, interpretation, and analysis.

KW - Artificial intelligence

KW - Computed tomography

KW - Deep learning

KW - Diagnosis

KW - Machine learning

KW - Prognosis

UR - https://www.scopus.com/pages/publications/85125978821

U2 - 10.1016/B978-0-12-820273-9.00009-9

DO - 10.1016/B978-0-12-820273-9.00009-9

M3 - Chapter (Book)

AN - SCOPUS:85125978821

SP - 211

EP - 239

BT - Machine Learning in Cardiovascular Medicine

A2 - J. Al'Aref, Subhi

A2 - Singh, Gurpreet

A2 - Baskaran, Lohendran

A2 - Metaxas, Dimitris

PB - Elsevier

CY - London UK

ER -

Computed tomography and artificial intelligence

Abstract

Keywords

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