Abdomen and spinal cord segmentation with augmented active shape models

Zhoubing Xu; Benjamin N. Conrad; Rebeccah B. Baucom; Seth A. Smith; Benjamin K. Poulose; Bennett A. Landman

doi:10.1117/1.JMI.3.3.036002

26 August 2016 Abdomen and spinal cord segmentation with augmented active shape models

Zhoubing Xu, Benjamin N. Conrad, Rebeccah B. Baucom, Seth A. Smith, Benjamin K. Poulose, Bennett A. Landman

Author Affiliations +

Journal of Medical Imaging, Vol. 3, Issue 3, 036002 (August 2016). https://doi.org/10.1117/1.JMI.3.3.036002

Abstract

Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC.

Citation Download Citation

Zhoubing Xu, Benjamin N. Conrad, Rebeccah B. Baucom, Seth A. Smith, Benjamin K. Poulose, and Bennett A. Landman "Abdomen and spinal cord segmentation with augmented active shape models," Journal of Medical Imaging 3(3), 036002 (26 August 2016). https://doi.org/10.1117/1.JMI.3.3.036002

Published: 26 August 2016

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