Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
466675 | Computer Methods and Programs in Biomedicine | 2012 | 16 Pages |
Abdominal aortic aneurysm (AAA) is a localized dilatation of the aortic wall. Accurate measurements of its geometric characteristics are critical for a reliable estimate of AAA rupture risk. However, current imaging modalities do not provide sufficient contrast to distinguish thrombus from surrounding tissue thus making the task of segmentation quite challenging. The main objective of this paper is to address this problem and accurately extract the thrombus and outer wall boundaries from cross sections of a 3D AAA image data set (CTA). This is achieved by new geometrical methods applied to the boundary curves obtained by a Level Set Method (LSM). Such methods address the problem of leakage of a moving front into sectors of similar intensity and that of the presence of calcifications. The versatility of the methods is tested by creating artificial images which simulate the real cases. Segmentation quality is quantified by comparing the results with a manual segmentation of the slices of ten patient data sets. Sensitivity to the parameter settings and reproducibility are analyzed. This is the first work to our knowledge that utilizes the level set framework to extract both the thrombus and external AAA wall boundaries.
► Geometrical methods are utilised to extract aortic aneurysm thrombus-wall boundary. ► Wall calcifications are exploited to extract inner and outer wall boundaries. ► Effective stopping criteria for leakage region detection are developed. ► Reliable wall thickness measurements are obtained with minimal user intervention.