AN iterative model-constrained graph-cut algorithm for Abdominal Aortic Aneurysm thrombus segmentation

Abstract

We present an iterative model-constrained graph-cut algorithm for the segmentation of Abdominal Aortic Aneurysm (AAA) thrombus. Given an initial segmentation of the aortic lumen, our method automatically segments the thrombus by iteratively coupling intensity-based graph min-cut segmentation and geometric parametric model fitting. The geometric model effectively constrains the graph min-cut segmentation from “leaking” to nearby veins and organs. Experimental results on 8 AAA CTA datasets yield robust segmentations of the AAA thrombus in 2 mins computer time with a mean absolute volume difference of 8.0% and mean volumetric overlap error of 12.9%, which is comparable to the interobserver error.