Evaluation of internal carotid artery segmentation by InsightSNAP

Emily L. Spangler; Christopher Brown; John A. Roberts; Brian E. Chapman

doi:10.1117/12.709954

8 March 2007 Evaluation of internal carotid artery segmentation by InsightSNAP

Emily L. Spangler, Christopher Brown, John A. Roberts, Brian E. Chapman

Proceedings Volume 6512, Medical Imaging 2007: Image Processing; 65123F (2007) https://doi.org/10.1117/12.709954
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

Quantification of cervical carotid geometry may facilitate improved clinical decision making and scientific discovery. We set out to evaluate the ability of InsightSNAP (ITK-SNAP), an open-source segmentation program for 3D medical images (http://www.itksnap.org, version 1.4), to semi-automatically segment internal carotid arteries. A sample of five individuals (three normal volunteers, and two diseased patients) were imaged with an MR exam consisting of a MOTSA TOF MRA image volume and multiple black blood images acquired with different contrast weightings. Comparisons were made to a manual segmentation created during simultaneous evaluation of the MOTSA image and the various black blood images (typically PD-weighted, T1-weighted, and T2-weighted). These individuals were selected as a training set to determine acceptable parameters for ITK-SNAP's semi-automatic level sets segmentation method. The conclusion from this training set was that the initial thresholding (assigning probabilities to the intensities of image pixels) in the image pre-processing step was most important to obtaining an acceptable segmentation. Unfortunately no consistent trends emerged in how this threshold should be chosen. Figures of percent over- and under-segmentation were computed as a means of comparing the hand segmented and semi-automatically segmented internal carotids. Overall the under-segmentation by ITK-SNAP (voxels included in the manual segmentation but not in the semiautomated segmentation) was 10.94% ± 6.35% while the over-segmentation (voxels excluded in the manual segmentation but included in the semi-automated segmentation) was 8.16% ± 4.40% defined by reference to the total number of voxels included in the manual segmentation.

Citation Download Citation

Emily L. Spangler, Christopher Brown, John A. Roberts, and Brian E. Chapman "Evaluation of internal carotid artery segmentation by InsightSNAP", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65123F (8 March 2007); https://doi.org/10.1117/12.709954

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available