Yes / The purpose of this work is to report on a machine vision approach for the automated measurement of x-ray
image contrast of coronary arteries lled with iodine contrast media during interventional cardiac procedures.
A machine vision algorithm was developed that creates a binary mask of the principal vessels of the coronary
artery tree by thresholding a standard deviation map of the direction image of the cardiac scene derived using a
Frangi lter. Using the mask, average contrast is calculated by tting a Gaussian model to the greyscale pro le
orthogonal to the vessel centre line at a number of points along the vessel. The algorithm was applied to sections
of single image frames from 30 left and 30 right coronary artery image sequences from di erent patients. Manual
measurements of average contrast were also performed on the same images. A Bland-Altman analysis indicates
good agreement between the two methods with 95% con dence intervals -0.046 to +0.048 with a mean bias of
0.001. The machine vision algorithm has the potential of providing real-time context sensitive information so
that radiographic imaging control parameters could be adjusted on the basis of clinically relevant image content. / Project PANORAMA, funded by grants from Belgium, Italy, France, the Netherlands, and the United Kingdom, and the ENIAC Joint Undertaking.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/16976 |
| Date | 16 March 2015 |
| Creators | Kengyelics, S.M., Gislason-Lee, Amber J., Keeble, C., Magee, D., Davies, A.G. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Conference paper, Accepted manuscript |
| Rights | (c) 2015, Society of Photo-Optical Instrumentation Engineers (SPIE). This is an author produced version of a paper published in Proceedings of SPIE 9399, Image Processing: Algorithms and Systems XIII. |
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