A hybrid method based on level set and 3D region growing for segmentation of the thoracic aorta

• Published in: Computer aided surgery (New York, N.Y.) Vol. 18; no. 5-6; pp. 109 - 117
• Main Authors: Martínez-Mera, Juan Antonio, Tahoces, Pablo G., Carreira, José M., Suárez-Cuenca, Jorge Juan, Souto, Miguel
• Format: Journal Article
• Language: English
• Published: England Informa UK Ltd 01.01.2013; Taylor & Francis
• Subjects: Algorithms; aneurysm; Angiography; Aorta; Aorta, Thoracic - diagnostic imaging; Aorta, Thoracic - pathology; Aortic Aneurysm, Thoracic - diagnostic imaging; Aortic Aneurysm, Thoracic - pathology; Aortic Aneurysm, Thoracic - surgery; Cohort Studies; computed tomography; Female; Humans; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; level set; Male; Middle Aged; Organ Size; segmentation; Tomography, X-Ray Computed
• ISSN: 1092-9088; 1097-0150
• DOI: 10.3109/10929088.2013.816978

Abstract This study sought to develop a completely automatic method for image segmentation of the thoracic aorta. We used a total of 4682 images from 10 consecutive patients. The proposed method is based on the use of level set and region growing, automatically initialized using the Hough transform. The results obtained were compared to those of manual segmentation as performed by an external expert radiologist. Concordance between the developed method and manual segmentation ranged from 92.79 to 95.77% in the descending regions of the aorta and from 90.68 to 96.54% in the ascending regions, with a mean value of 93.83% being obtained for total segmentation.