An iterative model-constrained graph-cut algorithm for abdominal aortic aneurysm thrombus segmentation

Authors:
Moti Freiman;Steven J. Esses;Leo Joskowicz;Jacob Sosna
Affiliations:
School of Engineering and Computer Science, The Hebrew University of Jerusalem, Israel;Mount Sinai School of Medicine, New York, NY and Dept. of Radiology, Hadassah Hebrew University Medical Center, Jerusalem, Israel;School of Engineering and Computer Science, The Hebrew University of Jerusalem, Israel;Dept. of Radiology, Hadassah Hebrew University Medical Center, Jerusalem, Israel
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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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.