Coronary artery tree segmentation in computed tomography angiography using Otsu method
Marwa Shams; Mohammed AM Salem; Hamad, Safwat; Howida A Shedeed;
Abstract
Analysis of coronary artery in medical images has been regarded as crucial step in the
assessment of cardiovascular diseases during clinical diagnosis and surgical planning.
Segmentation of coronaries in medical images is the most important step in such analysis. In
this paper, an automatic segmentation method is presented for segmenting coronary artery
lumen in Computed Tomography Angiography (CTA) datasets. Our proposed segmentation
approach consists of two main steps. The first one is an enhancement step to enhance
coronary vessels. The second is the coronary segmentation step done by applying Otsu
method. Otsu thresholding is applied with different number of thresholds to check the proper
number of thresholds that can better identify coronary vessel regions. Experiments are
carried out on 18 real CTA datasets. Segmentation results are quantitatively evaluated
assessment of cardiovascular diseases during clinical diagnosis and surgical planning.
Segmentation of coronaries in medical images is the most important step in such analysis. In
this paper, an automatic segmentation method is presented for segmenting coronary artery
lumen in Computed Tomography Angiography (CTA) datasets. Our proposed segmentation
approach consists of two main steps. The first one is an enhancement step to enhance
coronary vessels. The second is the coronary segmentation step done by applying Otsu
method. Otsu thresholding is applied with different number of thresholds to check the proper
number of thresholds that can better identify coronary vessel regions. Experiments are
carried out on 18 real CTA datasets. Segmentation results are quantitatively evaluated
Other data
| Title | Coronary artery tree segmentation in computed tomography angiography using Otsu method | Authors | Marwa Shams ; Mohammed AM Salem ; Hamad, Safwat ; Howida A Shedeed | Issue Date | 5-Dec-2017 | Publisher | IEEE | Conference | IEEE Eighth International Conference on Intelligent Computing and Information Systems (ICICIS 2017) |
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