ORBIT: A multiresolution framework for deformable registration of brain tumor images

Evangelia I. Zacharaki; Dinggang Shen; Seung Koo Lee; Christos Davatzikos

doi:10.1109/TMI.2008.916954

ORBIT: A multiresolution framework for deformable registration of brain tumor images

Evangelia I. Zacharaki
, Dinggang Shen
, Seung Koo Lee
, Christos Davatzikos

Research output: Contribution to journal › Article › peer-review

98 Citations (Scopus)

Abstract

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.

Original language	English
Article number	4436040
Pages (from-to)	1003-1017
Number of pages	15
Journal	IEEE Transactions on Medical Imaging
Volume	27
Issue number	8
DOIs	https://doi.org/10.1109/TMI.2008.916954
Publication status	Published - 2008 Aug

Bibliographical note

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: [email protected]).

Keywords

Atlas registration
Brain tumor
Deformable registration
Image attributes
Tumor growth model

ASJC Scopus subject areas

Software
Radiological and Ultrasound Technology
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TMI.2008.916954

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title = "ORBIT: A multiresolution framework for deformable registration of brain tumor images",

abstract = "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.",

keywords = "Atlas registration, Brain tumor, Deformable registration, Image attributes, Tumor growth model",

author = "Zacharaki, \{Evangelia I.\} and Dinggang Shen and Lee, \{Seung Koo\} and Christos Davatzikos",

note = "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: [email protected]).",

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doi = "10.1109/TMI.2008.916954",

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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: [email protected]).

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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.

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KW - Image attributes

KW - Tumor growth model

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ORBIT: A multiresolution framework for deformable registration of brain tumor images

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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