Share Email Print
cover

Proceedings Paper

Parallel optimization of tumor model parameters for fast registration of brain tumor images
Author(s): Evangelia I. Zacharaki; Cosmina S. Hogea; Dinggang Shen; George Biros; Christos Davatzikos
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The motivation of this work is to register MR brain tumor images with a brain atlas. Such a registration method can make possible the pooling of data from different brain tumor patients into a common stereotaxic space, thereby enabling the construction of statistical brain tumor atlases. Moreover, it allows the mapping of neuroanatomical brain atlases into the patient's space, for segmenting brains and thus facilitating surgical or radiotherapy treatment planning. However, the methods developed for registration of normal brain images are not directly applicable to the registration of a normal atlas with a tumor-bearing image, due to substantial dissimilarity and lack of equivalent image content between the two images, as well as severe deformation or shift of anatomical structures around the tumor. Accordingly, a model that can simulate brain tissue death and deformation induced by the tumor is considered to facilitate the registration. Such tumor growth simulation models are usually initialized by placing a small seed in the normal atlas. The shape, size and location of the initial seed are critical for achieving topological equivalence between the atlas and patient's images. In this study, we focus on the automatic estimation of these parameters, pertaining to tumor simulation. In particular, we propose an objective function reflecting feature-based similarity and elastic stretching energy and optimize it with APPSPACK (Asynchronous Parallel Pattern Search), for achieving significant reduction of the computational cost. The results indicate that the registration accuracy is high in areas around the tumor, as well as in the healthy portion of the brain.

Paper Details

Date Published: 11 March 2008
PDF: 10 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69140K (11 March 2008); doi: 10.1117/12.767788
Show Author Affiliations
Evangelia I. Zacharaki, Univ. of Pennsylvania (United States)
Cosmina S. Hogea, Univ. of Pennsylvania (United States)
Dinggang Shen, Univ. of Pennsylvania (United States)
George Biros, Univ. of Pennsylvania (United States)
Christos Davatzikos, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

© SPIE. Terms of Use
Back to Top