Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort

Daniel Lorenzatti; Annalisa Filtz; Pamela Pina; Andrea Scotti; Aldo L. Schenone; Carlos A. Gongora; Alan C. Kwan; Victor Y. Cheng; Mario J. Garcia; Daniel S. Berman; Piotr J. Slomka; Damini Dey; Leandro Slipczuk

doi:10.1016/j.jcct.2024.03.012

Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort

Daniel Lorenzatti, Annalisa Filtz, Pamela Pina, Andrea Scotti, Aldo L. Schenone, Carlos A. Gongora, Alan C. Kwan, Victor Y. Cheng, Mario J. Garcia, Daniel S. Berman, Piotr J. Slomka, Damini Dey, Leandro Slipczuk

Research output: Contribution to journal › Letter › peer-review

Original language	English
Pages (from-to)	507-509
Number of pages	3
Journal	Journal of Cardiovascular Computed Tomography
Volume	18
Issue number	5
DOIs	https://doi.org/10.1016/j.jcct.2024.03.012
State	Published - 1 Sep 2024
Externally published	Yes

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10.1016/j.jcct.2024.03.012

Cite this

Lorenzatti, D., Filtz, A., Pina, P., Scotti, A., Schenone, A. L., Gongora, C. A., Kwan, A. C., Cheng, V. Y., Garcia, M. J., Berman, D. S., Slomka, P. J., Dey, D., & Slipczuk, L. (2024). Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort. Journal of Cardiovascular Computed Tomography, 18(5), 507-509. https://doi.org/10.1016/j.jcct.2024.03.012

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title = "Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort",

author = "Daniel Lorenzatti and Annalisa Filtz and Pamela Pina and Andrea Scotti and Schenone, {Aldo L.} and Gongora, {Carlos A.} and Kwan, {Alan C.} and Cheng, {Victor Y.} and Garcia, {Mario J.} and Berman, {Daniel S.} and Slomka, {Piotr J.} and Damini Dey and Leandro Slipczuk",

year = "2024",

month = sep,

day = "1",

doi = "10.1016/j.jcct.2024.03.012",

language = "English",

volume = "18",

pages = "507--509",

journal = "Journal of Cardiovascular Computed Tomography",

issn = "1934-5925",

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}

Lorenzatti, D, Filtz, A, Pina, P, Scotti, A, Schenone, AL, Gongora, CA, Kwan, AC, Cheng, VY, Garcia, MJ, Berman, DS, Slomka, PJ, Dey, D & Slipczuk, L 2024, 'Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort', Journal of Cardiovascular Computed Tomography, vol. 18, no. 5, pp. 507-509. https://doi.org/10.1016/j.jcct.2024.03.012

Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort. / Lorenzatti, Daniel; Filtz, Annalisa; Pina, Pamela et al.
In: Journal of Cardiovascular Computed Tomography, Vol. 18, No. 5, 01.09.2024, p. 507-509.

Research output: Contribution to journal › Letter › peer-review

TY - JOUR

T1 - Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort

AU - Lorenzatti, Daniel

AU - Filtz, Annalisa

AU - Pina, Pamela

AU - Scotti, Andrea

AU - Schenone, Aldo L.

AU - Gongora, Carlos A.

AU - Kwan, Alan C.

AU - Cheng, Victor Y.

AU - Garcia, Mario J.

AU - Berman, Daniel S.

AU - Slomka, Piotr J.

AU - Dey, Damini

AU - Slipczuk, Leandro

PY - 2024/9/1

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U2 - 10.1016/j.jcct.2024.03.012

DO - 10.1016/j.jcct.2024.03.012

M3 - Letter

C2 - 38553402

AN - SCOPUS:85190450827

SN - 1934-5925

VL - 18

SP - 507

EP - 509

JO - Journal of Cardiovascular Computed Tomography

JF - Journal of Cardiovascular Computed Tomography

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ER -