Three-dimensional thrombus segmentation in abdominal aortic aneurysms using graph search based on a triangular mesh

Authors:
Kyungmoo Lee;Ryan K. Johnson;Yin Yin;Andreas Wahle;Mark E. Olszewski;Thomas D. Scholz;Milan Sonka
Affiliations:
Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA, USA;Division of Pediatric Cardiology, University of Iowa Hospitals & Clinics, Iowa City, IA, USA;Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA, USA;Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA, USA;CT Clinical Science, Philips Healthcare, Cleveland, OH, USA;Division of Pediatric Cardiology, University of Iowa Hospitals & Clinics, Iowa City, IA, USA;Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA, USA
Venue:
Computers in Biology and Medicine
Year:
2010

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Abstract

An abdominal aortic aneurysm (AAA) is the area of a localized widening of the abdominal aorta, with a frequent presence of thrombus. Segmentation and quantitative analysis of the thrombus in AAA are of paramount importance for diagnosis, risk assessment and determination of treatment options. The proposed thrombus segmentation method utilizes the power and flexibility of the 3-D graph search approach based on a triangular mesh. The method was tested in 9 3-D MDCT angiography data sets (9 patients with AAA, 1300 image slices), and the mean unsigned errors for the luminal and thrombotic surfaces were 0.99+/-0.18mm and 1.90+/-0.72mm. To achieve these results, 9.9+/-10.3 control points needed to be interactively entered on 2.1+/-2.2 image slices per 3-D CTA data set.