Simultaneous segmentation and motion estimation in 4D-CT data using a variational approach

Jan Ehrhardt; Alexander Schmidt-Richberg; Heinz Handels

doi:10.1117/12.768228

11 March 2008 Simultaneous segmentation and motion estimation in 4D-CT data using a variational approach

Jan Ehrhardt, Alexander Schmidt-Richberg, Heinz Handels

Author Affiliations +

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 691437 (2008) https://doi.org/10.1117/12.768228
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Spatiotemporal image data sets, like 4D CT or dynamic MRI, open up the possibility to estimate respiratory induced tumor and organ motion and to generate four-dimensional models that describe the temporal change in position and shape of structures of interest. However, two main problems arise: the structures of interest have to be segmented in the 4D data set and and the organ motion has to be estimated in the temporal image sequence. This paper presents a variational approach for simultaneous segmentation and registration applied to temporal image sequences. The proposed method assumes a known segmentation in one frame and then recovers nonlinear registration and segmentation in other frames by minimizing a cost function that combines intensity-based registration, level-set segmentation as well as prior shape and intensity knowledge. The purpose of the presented method is to estimate respiration induced organ motion in spatiotemporal CT image sequences and to segment a structure of interest simultaneously. A validation of the combined registration and segmentation approach is presented using low dose 4D CT data sets of the liver. The results demonstrate that the simultaneous solution of both problems improves the segmentation performance over a sequential application of the registration and segmentation steps.

Citation Download Citation

Jan Ehrhardt, Alexander Schmidt-Richberg, and Heinz Handels "Simultaneous segmentation and motion estimation in 4D-CT data using a variational approach", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691437 (11 March 2008); https://doi.org/10.1117/12.768228

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