prikaz prve stranice dokumenta A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework
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Scientific paper - Review paper
A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework
Journal of Digital Imaging, 34 (2021), 3; 581-604. https://doi.org/10.1007/s10278-021-00461-2
Biswas, Mainak; Saba, Luca; Omerzu, Toma; Johri, Amer M; N Khanna, Narendra; Viskovic, Klaudija; Mavrogeni, Sophie; R Laird, John; Pareek, Gyan; Miner, Martin; Balestrieri, Antonella; P Sfikakis, Petros P; Protogerou, Athanasios; Prasanna Misra, Durga; Agarwal, Vikas; D Kitas, George; Kolluri, Raghu; Sharma, Aditya; Viswanathan, Vijay; Ruzsa, Zoltan; Nicolaides, Andrew; S Suri, Jasjit More authors...

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Biswas, M., Saba, L., Omerzu, T., Johri, A. M., N Khanna, N., Viskovic, K. ... S Suri, J. (2021). A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework. Journal of Digital Imaging, 34. (3), 581-604. doi: 10.1007/s10278-021-00461-2

Biswas, Mainak, et al. "A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework." Journal of Digital Imaging, vol. 34, no. 3, 2021, pp. 581-604. https://doi.org/10.1007/s10278-021-00461-2

Biswas, Mainak, Luca Saba, Toma Omerzu, Amer M Johri, Narendra N Khanna, Klaudija Viskovic, Sophie Mavrogeni, et al. "A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework." Journal of Digital Imaging 34, no. 3 (2021): 581-604. https://doi.org/10.1007/s10278-021-00461-2

Biswas, M., et al. (2021) 'A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework', Journal of Digital Imaging, 34(3), pp. 581-604. doi: 10.1007/s10278-021-00461-2

Biswas M, Saba L, Omerzu T, Johri AM, N Khanna N, Viskovic K, and sur.. A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework. Journal of Digital Imaging [Internet]. 2021 June [cited 2024 November 11];34(3):581-604. doi: 10.1007/s10278-021-00461-2

M. Biswas, et al., "A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework", Journal of Digital Imaging, vol. 34, no. 3, pp. 581-604, June 2021. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:184:092873. [Accessed: 11 November 2024]

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Metadata
Title (english)A Review on Joint Carotid Intima‑Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework
AuthorMainak Biswas
AuthorLuca Saba
AuthorToma Omerzu
AuthorAmer M Johri
AuthorNarendra N Khanna
AuthorKlaudija Viskovic
AuthorSophie Mavrogeni
AuthorJohn R Laird
AuthorGyan Pareek
AuthorMartin Miner
AuthorAntonella Balestrieri
AuthorPetros P P Sfikakis
AuthorAthanasios Protogerou
AuthorDurga Prasanna Misra
AuthorVikas Agarwal
AuthorGeorge D Kitas
AuthorRaghu Kolluri
AuthorAditya Sharma
AuthorVijay Viswanathan
AuthorZoltan Ruzsa
AuthorAndrew Nicolaides
AuthorJasjit S Suri
Author's institutionUniversity of Rijeka
Faculty of Health Studies
(Department of Laboratory and Radiological Diagnostics)
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Clinical Medical Sciences
Internal Medicine
Abstract (english)
Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide. Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial infarction and stroke. The two primary image-based phenotypes used for monitoring the atherosclerosis burden is carotid intima-media thickness (cIMT) and plaque area (PA). Earlier segmentation and measurement methods were based on ad hoc conventional and semi-automated digital imaging solutions, which are unreliable, tedious, slow, and not robust. This study reviews the modern and automated methods such as artificial intelligence (AI)-based. Machine learning (ML) and deep learning (DL) can provide automated techniques in the detection and measurement of cIMT and PA from carotid vascular images. Both ML and DL techniques are examples of supervised learning, i.e., learn from "ground truth" images and transformation of test images that are not part of the training. This review summarizes (1) the evolution and impact of the fast-changing AI technology on cIMT/PA measurement, (2) the mathematical representations of ML/DL methods, and (3) segmentation approaches for cIMT/PA regions in carotid scans based for (a) region-of-interest detection and (b) lumen-intima and media-adventitia interface detection using ML/DL frameworks. AI-based methods for cIMT/PA segmentation have emerged for CVD/stroke risk monitoring and may expand to the recommended parameters for atherosclerosis assessment by carotid ultrasound.
Keywords (english)
Languageenglish
Publication typeScientific paper - Review paper
Publication statusPublished
Peer reviewPeer review
Publication versionPublished version
Journal titleJournal of Digital Imaging
Numberingvol. 34, no. 3, pp. 581-604
p-ISSN0897-1889
e-ISSN1618-727X
DOIhttps://doi.org/10.1007/s10278-021-00461-2
URN:NBNurn:nbn:hr:184:092873
Publication2021-06
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-07-07 11:43:29