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Improved CTA Coronary Segmentation with a Volume-Specific Intensity Threshold

Jawaid, M. M., Rajani, R., Liatsis, P. , Reyes-Aldasoro, C. C. ORCID: 0000-0002-9466-2018 & Slabaugh, G. G. (2017). Improved CTA Coronary Segmentation with a Volume-Specific Intensity Threshold. Paper presented at the Medical Image Understanding and Analysis (MIUA) 2017, 11 Jul 2017, Edinburgh, UK.

Abstract

State-of-the-art CTA imaging equipment has increased increased clinician's ability to make non-invasive diagnoses of coronary heart disease; however, an effective interpretation of the cardiac CTA becomes cumbersome due to large amount of imaged data. Intensity based background suppression is often used to enhance the coronary vasculature but setting a fixed threshold to discriminate coronaries from fatty muscles could be misleading due to non-homogeneous response of contrast medium in CTA volumes. In this work, we propose a volumespecific model of the contrast medium in the coronary segmentation process to improve the segmentation accuracy. The influence of the contrast medium in a CTA volume was modelled by approximating the intensity histogram of the descending aorta with Gaussian approximation. It should be noted that a significant variation in Gaussian mean for 12 CTA volumes validates the need of volume-wise exclusive intensity threshold for accurate coronary segmentation. Moreover, the effectiveness of the adaptive intensity threshold is illustrated with the help of qualitative and quantitative results.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-60964-5_18.
Publisher Keywords: computed tomography angiography, contrast medium, curve evolution, coronary segmentation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Departments: School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > giCentre
School of Science & Technology > Engineering
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