TY - JOUR
T1 - ORBIT
T2 - A multiresolution framework for deformable registration of brain tumor images
AU - Zacharaki, Evangelia I.
AU - Shen, Dinggang
AU - Lee, Seung Koo
AU - Davatzikos, Christos
N1 - Funding Information:
Manuscript received June 29, 2007; revised November 26, 2007. First published February 2, 2008; last published July 25, 2008 (projected). This work was supported by the National Institutes of Health under Grant NS042645. Asterisk indicates corresponding author. *E. I. Zacharaki is with the Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, 3600 Market Street, Philadelphia, PA 19104 USA (e-mail: eva.zacharaki@uphs.upenn.edu).
PY - 2008/8
Y1 - 2008/8
N2 - A deformable registration method is proposed for registering a normal brain atlas with images of brain tumor patients. The registration is facilitated by first simulating the tumor mass effect in the normal atlas in order to create an atlas image that is as similar as possible to the patient's image. An optimization framework is used to optimize the location of tumor seed as well as other parameters of the tumor growth model, based on the pattern of deformation around the tumor region. In particular, the optimization is implemented in a multiresolution and hierarchical scheme, and it is accelerated by using a principal component analysis (PCA)-based model of tumor growth and mass effect, trained on a computationally more expensive biomechanical model. Validation on simulated and real images shows that the proposed registration framework, referred to as ORBIT (optimization of tumor parameters and registration of brain images with tumors), outperforms other available registration methods particularly for the regions close to the tumor, and it has the potential to assist in constructing statistical atlases from tumor-diseased brain images.
AB - A deformable registration method is proposed for registering a normal brain atlas with images of brain tumor patients. The registration is facilitated by first simulating the tumor mass effect in the normal atlas in order to create an atlas image that is as similar as possible to the patient's image. An optimization framework is used to optimize the location of tumor seed as well as other parameters of the tumor growth model, based on the pattern of deformation around the tumor region. In particular, the optimization is implemented in a multiresolution and hierarchical scheme, and it is accelerated by using a principal component analysis (PCA)-based model of tumor growth and mass effect, trained on a computationally more expensive biomechanical model. Validation on simulated and real images shows that the proposed registration framework, referred to as ORBIT (optimization of tumor parameters and registration of brain images with tumors), outperforms other available registration methods particularly for the regions close to the tumor, and it has the potential to assist in constructing statistical atlases from tumor-diseased brain images.
KW - Atlas registration
KW - Brain tumor
KW - Deformable registration
KW - Image attributes
KW - Tumor growth model
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U2 - 10.1109/TMI.2008.916954
DO - 10.1109/TMI.2008.916954
M3 - Article
C2 - 18672419
AN - SCOPUS:43449092116
SN - 0278-0062
VL - 27
SP - 1003
EP - 1017
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 8
M1 - 4436040
ER -