Magnetic resonance imaging and artificial intelligence

Giuseppe Muscogiuri; Marco Guglielmo; Andrea Baggiano; Laura Fusini; Francesca Ricci; Gloria Cicala; Mark G. Rabbat; Andrea I. Guaricci; Gianluca Pontone

doi:10.1016/B978-0-12-820273-9.00010-5

Magnetic resonance imaging and artificial intelligence

Giuseppe Muscogiuri, Marco Guglielmo, Andrea Baggiano, Laura Fusini, Francesca Ricci, Gloria Cicala, Mark G. Rabbat, Andrea I. Guaricci, Gianluca Pontone

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

Abstract

Cardiac magnetic resonance (CMR) is the best-suited cardiac imaging modality to provide reliable and reproducible information regarding cardiac volumes, function, and tissue characterization. In clinical practice, artificial intelligence (AI) in CMR can be applied to the whole process, ranging from sequence reconstruction, image analysis, and reporting of findings. In sequence reconstruction, the application of AI is mainly focused on the speed of reconstruction, while in image analysis and reporting AI is primarily aimed at automating the process of segmentation of both ventricles as well as fibrotic tissue. Within the realm of tissue characterization, AI can also be helpful in the depiction of tissue abnormalities from noncontrast images. Finally, AI can be useful for prognostic stratification.

Original language	English
Title of host publication	Machine Learning in Cardiovascular Medicine
Publisher	Elsevier
Pages	241-253
Number of pages	13
ISBN (Electronic)	9780128202739
DOIs	https://doi.org/10.1016/B978-0-12-820273-9.00010-5
Publication status	Published - 1 Jan 2020
Externally published	Yes

Keywords

Artificial intelligence
Cardiac magnetic resonance
Diagnosis
Function
Myocardial tissue characterization
Prognosis

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10.1016/B978-0-12-820273-9.00010-5

Cite this

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abstract = "Cardiac magnetic resonance (CMR) is the best-suited cardiac imaging modality to provide reliable and reproducible information regarding cardiac volumes, function, and tissue characterization. In clinical practice, artificial intelligence (AI) in CMR can be applied to the whole process, ranging from sequence reconstruction, image analysis, and reporting of findings. In sequence reconstruction, the application of AI is mainly focused on the speed of reconstruction, while in image analysis and reporting AI is primarily aimed at automating the process of segmentation of both ventricles as well as fibrotic tissue. Within the realm of tissue characterization, AI can also be helpful in the depiction of tissue abnormalities from noncontrast images. Finally, AI can be useful for prognostic stratification.",

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AU - Muscogiuri, Giuseppe

AU - Guglielmo, Marco

AU - Baggiano, Andrea

AU - Fusini, Laura

AU - Ricci, Francesca

AU - Cicala, Gloria

AU - Rabbat, Mark G.

AU - Guaricci, Andrea I.

AU - Pontone, Gianluca

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AB - Cardiac magnetic resonance (CMR) is the best-suited cardiac imaging modality to provide reliable and reproducible information regarding cardiac volumes, function, and tissue characterization. In clinical practice, artificial intelligence (AI) in CMR can be applied to the whole process, ranging from sequence reconstruction, image analysis, and reporting of findings. In sequence reconstruction, the application of AI is mainly focused on the speed of reconstruction, while in image analysis and reporting AI is primarily aimed at automating the process of segmentation of both ventricles as well as fibrotic tissue. Within the realm of tissue characterization, AI can also be helpful in the depiction of tissue abnormalities from noncontrast images. Finally, AI can be useful for prognostic stratification.

KW - Artificial intelligence

KW - Cardiac magnetic resonance

KW - Diagnosis

KW - Function

KW - Myocardial tissue characterization

KW - Prognosis

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BT - Machine Learning in Cardiovascular Medicine

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Magnetic resonance imaging and artificial intelligence

Abstract

Keywords

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