Why the study?
Does automatic analysis of four-dimensional ultrasonographic data accurately classify carotid disease severity in patients and healthy volunteers?
Does automatic analysis of four-dimensional ultrasonographic data accurately classify carotid disease severity in patients and healthy volunteers?
Automated analysis of four-dimensional ultrasound data shows promise for accurately classifying carotid artery disease severity, particularly for healthy individuals and those with complete occlusions.
Supports automated 4D ultrasound carotid classification in small cohorts; leaves open clinical adoption pending prospective validation.
Automatic analysis was performed of four-dimensional ultrasonographic (US) data in the carotid artery. The data, which were acquired in 31 subjects (eight healthy volunteers and 23 patients) by using a US scanner fitted with a special probe, were successfully processed. Acquisition time averaged 12 minutes. Data for all healthy volunteers (n = 8) and patients with complete occlusions (n = 3) were correctly classified. Data for two of the 12 patients with mild to severe (but not occlusive) disease were misclassified by one category.
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Napel et al. (2002) studied this question.
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