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Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol

Research output: Contribution to journalArticleScientificpeer-review

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Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. / Caetano Dos Santos, Florentino Luciano; Joutsen, Atte; Paci, Michelangelo; Salenius, Juha; Eskola, Hannu.

In: International Journal of Cardiovascular Imaging, Vol. 32, No. 8, 08.2016, p. 1299–1310.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Caetano Dos Santos, FL, Joutsen, A, Paci, M, Salenius, J & Eskola, H 2016, 'Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol', International Journal of Cardiovascular Imaging, vol. 32, no. 8, pp. 1299–1310. https://doi.org/10.1007/s10554-016-0880-6

APA

Caetano Dos Santos, F. L., Joutsen, A., Paci, M., Salenius, J., & Eskola, H. (2016). Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. International Journal of Cardiovascular Imaging, 32(8), 1299–1310. https://doi.org/10.1007/s10554-016-0880-6

Vancouver

Caetano Dos Santos FL, Joutsen A, Paci M, Salenius J, Eskola H. Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. International Journal of Cardiovascular Imaging. 2016 Aug;32(8):1299–1310. https://doi.org/10.1007/s10554-016-0880-6

Author

Caetano Dos Santos, Florentino Luciano ; Joutsen, Atte ; Paci, Michelangelo ; Salenius, Juha ; Eskola, Hannu. / Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. In: International Journal of Cardiovascular Imaging. 2016 ; Vol. 32, No. 8. pp. 1299–1310.

Bibtex - Download

@article{a3e62c437a574f259889b190a264024a,
title = "Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol",
abstract = "Atherosclerosis is one of the leading causes of mortality in the western world. Computed tomography angiography (CTA) is the conventional imaging method used for pre-surgery assessment of the blood flow within the carotid vessel. In this paper, we present a proof of concept of a novel, fast and operator independent protocol for the automatic detection (seeding) of the carotid arteries in CTA in the thorax and upper neck region. The dataset is composed of 14 patients’ CTA images of the neck region. The performance of this method is compared with manual seeding by four trained operators. Inter-operator variation is also assessed based on the dataset. The minimum, average and maximum coefficient of variation among the operators was (0, 2, 5 {\%}), respectively. The performance of our method is comparable with the state of the art alternative, presenting a detection rate of 75 and 71 {\%} for the lowest and uppermost image levels, respectively. The mean processing time is 167 s per patient versus 386 s for manual seeding. There are no significant differences between the manual and automatic seed positions in the volumes (p = 0.29). A fast, operator independent protocol was developed for the automatic detection of carotid arteries in CTA. The results are encouraging and provide the basis for the creation of automatic detection and analysis tools for carotid arteries.",
author = "{Caetano Dos Santos}, {Florentino Luciano} and Atte Joutsen and Michelangelo Paci and Juha Salenius and Hannu Eskola",
year = "2016",
month = "8",
doi = "10.1007/s10554-016-0880-6",
language = "English",
volume = "32",
pages = "1299–1310",
journal = "International Journal of Cardiovascular Imaging",
issn = "1569-5794",
publisher = "Springer Verlag",
number = "8",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol

AU - Caetano Dos Santos, Florentino Luciano

AU - Joutsen, Atte

AU - Paci, Michelangelo

AU - Salenius, Juha

AU - Eskola, Hannu

PY - 2016/8

Y1 - 2016/8

N2 - Atherosclerosis is one of the leading causes of mortality in the western world. Computed tomography angiography (CTA) is the conventional imaging method used for pre-surgery assessment of the blood flow within the carotid vessel. In this paper, we present a proof of concept of a novel, fast and operator independent protocol for the automatic detection (seeding) of the carotid arteries in CTA in the thorax and upper neck region. The dataset is composed of 14 patients’ CTA images of the neck region. The performance of this method is compared with manual seeding by four trained operators. Inter-operator variation is also assessed based on the dataset. The minimum, average and maximum coefficient of variation among the operators was (0, 2, 5 %), respectively. The performance of our method is comparable with the state of the art alternative, presenting a detection rate of 75 and 71 % for the lowest and uppermost image levels, respectively. The mean processing time is 167 s per patient versus 386 s for manual seeding. There are no significant differences between the manual and automatic seed positions in the volumes (p = 0.29). A fast, operator independent protocol was developed for the automatic detection of carotid arteries in CTA. The results are encouraging and provide the basis for the creation of automatic detection and analysis tools for carotid arteries.

AB - Atherosclerosis is one of the leading causes of mortality in the western world. Computed tomography angiography (CTA) is the conventional imaging method used for pre-surgery assessment of the blood flow within the carotid vessel. In this paper, we present a proof of concept of a novel, fast and operator independent protocol for the automatic detection (seeding) of the carotid arteries in CTA in the thorax and upper neck region. The dataset is composed of 14 patients’ CTA images of the neck region. The performance of this method is compared with manual seeding by four trained operators. Inter-operator variation is also assessed based on the dataset. The minimum, average and maximum coefficient of variation among the operators was (0, 2, 5 %), respectively. The performance of our method is comparable with the state of the art alternative, presenting a detection rate of 75 and 71 % for the lowest and uppermost image levels, respectively. The mean processing time is 167 s per patient versus 386 s for manual seeding. There are no significant differences between the manual and automatic seed positions in the volumes (p = 0.29). A fast, operator independent protocol was developed for the automatic detection of carotid arteries in CTA. The results are encouraging and provide the basis for the creation of automatic detection and analysis tools for carotid arteries.

U2 - 10.1007/s10554-016-0880-6

DO - 10.1007/s10554-016-0880-6

M3 - Article

VL - 32

SP - 1299

EP - 1310

JO - International Journal of Cardiovascular Imaging

JF - International Journal of Cardiovascular Imaging

SN - 1569-5794

IS - 8

ER -