DocumentCode
1364539
Title
Derivation of optimal filters for the detection of coronary arteries
Author
Van der Zwet, Pieter M J ; Nettesheim, Maurice ; Gerbrands, Jan J. ; Reiber, Johan H C
Author_Institution
Dept. of Radiol., Leiden Univ., Netherlands
Volume
17
Issue
1
fYear
1998
Firstpage
108
Lastpage
120
Abstract
Optimal filters for the detection of coronary arteries with a diameter range of 0.5-6.0 mm in digital X-ray images are derived using a computational approach. This approach is based on the two requirements for optimal detection. First, the filter should maximize the number of detected true edges and minimize the number of detected false edges. Second, if an edge has been detected, its position should be as close as possible to the true edge position in the image. Since the grey value profile in a digital X-ray image associated with an arterial vessel is asymmetric, the theory on edge detection derived by Canny has been expanded with two additional boundary constraints to make it suitable for the derivation of filters for asymmetric edges. It is demonstrated that it is possible to derive optimal filters for coronary segments. The localization error, defined by the square root of the sum of the squared systematic and random errors in the assessment of the arterial diameter, depends on the size of the coronary artery and the amount of noise in the image. Here, an evaluation study is described to assess the relationship between localization error and the amount of noise upon the vessel profile. For that purpose, an analytical description of the vessel profile in an angiographic image was derived. For the larger arteries the relation between noise and localization error was found to be linear and no systematic over- or underestimations were observed, even if the noise level was very high. However, it can be shown that the smallest diameter that can be measured depends on the amount of noise present in the data. Even for images that contain only a low amount of noise, arterial diameters below 0.7 mm cannot be measured accurately. If the noise in the image increases, the lowest measurable arterial diameter value also increases. Also the random error increases rapidly for vessel diameters below 1.2 mm, but with a limited amount of noise and a diameter value above 0.7 mm the- - random error is still acceptable [0.15 mm (21%) for 0.7-mm vessels, 0.06 mm (6%) for 1-mm vessels].
Keywords
cardiology; diagnostic radiography; diameter measurement; edge detection; matched filters; measurement errors; medical image processing; 0.5 to 6.0 mm; arterial vessel; boundary constraints; coronary arteries detection; coronary segments; detected false edges; detected true edges; digital X-ray images; grey value profile; localization error; medical diagnostic imaging; optimal filters derivation; random errors; systematic errors; Arteries; Constraint theory; Digital filters; Filtering theory; Image edge detection; Noise level; Noise measurement; X-ray detection; X-ray detectors; X-ray imaging; Coronary Angiography; Filtration; Humans; Models, Theoretical;
fLanguage
English
Journal_Title
Medical Imaging, IEEE Transactions on
Publisher
ieee
ISSN
0278-0062
Type
jour
DOI
10.1109/42.668700
Filename
668700
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