Automatic segmentation of abdominal wall in ventral hernia CT: a pilot study

Zhoubing Xu; Wade M. Allen; Benjamin K. Poulose; Bennett A. Landman

doi:10.1117/12.2007060

13 March 2013 Automatic segmentation of abdominal wall in ventral hernia CT: a pilot study

Zhoubing Xu, Wade M. Allen, Benjamin K. Poulose, Bennett A. Landman

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86693T (2013) https://doi.org/10.1117/12.2007060
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24-43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments; notably, quantitative metrics based on image-processing are not used. We propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore, to optimize intervention. To date, automated segmentation algorithms have not been presented to quantify the abdominal wall and potential hernias. In this pilot study with four clinically acquired CT scans on post-operative patients, we demonstrate a novel approach to geometric classification of the abdominal wall and essential abdominal features (including bony landmarks and skin surfaces). Our approach uses a hierarchical design in which the abdominal wall is isolated in the context of the skin and bony structures using level set methods. All segmentation results were quantitatively validated with surface errors based on manually labeled ground truth. Mean surface errors for the outer surface of the abdominal wall was less than 2mm. This approach establishes a baseline for characterizing the abdominal wall for improving VH care.

Citation Download Citation

Zhoubing Xu, Wade M. Allen, Benjamin K. Poulose, and Bennett A. Landman "Automatic segmentation of abdominal wall in ventral hernia CT: a pilot study", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693T (13 March 2013); https://doi.org/10.1117/12.2007060

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