Robust infrarenal aortic aneurysm lumen centerline detection for rupture status classification.

ABSTRACT: The objective of this work is to develop a robust method for human abdominal aortic aneurysm (AAA) centerline detection that can contribute to the accurate computation of features for the prediction of AAA rupture risk. A semiautomatic algorithm is proposed for detecting the lumen centerline in contrast-enhanced abdominal computed tomography images based on online adaboost classifiers, which does not require prior image segmentation. The algorithm was developed and applied to thirty ruptured and thirty unruptured AAA image data sets and the tortuosities of the detected centerline were measured to assess the correlation between AAA tortuosity and the binary ruptured and unruptured labels. The lumen of each data set was segmented manually by a trained radiologist and the resulting centerline

SUBMITTER: Zhang H 

PROVIDER: S-EPMC3776471 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature