Key result
Semi-automated CTA carotid lumen segmentation closely matches manual measurement with only ~2% difference.
Why the study?
A fast and reliable tool to quantify the severity of carotid artery stenosis using CTA images was needed to improve segmentation accuracy and efficiency.
Does a semi-automated segmentation method accurately segment the carotid lumen in CTA images compared to manual segmentation?
Does a semi-automated segmentation method accurately segment the carotid lumen in CTA images compared to manual segmentation?
Effect estimate: 2.14±2.08
A proposed semi-automated method for carotid lumen segmentation in CTA images provides a fast and reliable tool to quantify stenosis severity.
May accelerate CTA-based stenosis assessment; leaves open prospective clinical validation before routine use.
) = 2.14±2.08 between manual and automated segmentation of common, internal and external carotid arteries, carotid bifurcation and stenotic artery, respectively. Quantitative measurements showed that the proposed method has high potential to segment the carotid lumen and is robust to the changes of the lumen diameter and the shape of the stenosis area at the bifurcation site. The proposed method for CTA images provides a fast and reliable tool to quantify the severity of carotid artery stenosis.
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Hamid et al. (2017) studied Carotid artery stenosis. Semi-automated carotid lumen segmentation vs. Manual segmentation was evaluated on Difference between manual and automated segmentation (2.14±2.08). Semi-automated carotid lumen segmentation in CTA images demonstrated a difference of 2.14±2.08 compared to manual segmentation, providing a robust tool to quantify carotid artery stenosis.
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