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EN
Abdominal Aortic Aneurysm (AAA) is a local dilation of the Aorta that occurs between the renal and iliac arteries. Recently developed treatment involves the insertion of a endovascular prosthetic (EVAR), which has the advantage of being a minimally invasive procedure but also requires monitoring to analyze postoperative patient outcomes. The most widespread method for monitoring is computerized axial tomography (CAT) imaging, which allows 3D reconstructions and segmentations of the aorta's lumen of the patient under study. Previously published methods measure the deformation of the aorta between two studies of the same patient using image registration techniques. This paper applies neural network and statistical classifiers to build a predictor of patient survival. The features used for classification are the volume registration quality measures after each of the image registration steps. This system provides the medical team an additional decision support tool.
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