Registration of 3-D CT and 2-D flat images of mouse via affine transformation

Zheng Xia; Xishi Huang; Xiaobo Zhou; Youxian Sun; Vasilis Ntziachristos; Stephen T C Wong

doi:10.1109/TITB.2007.904631

Registration of 3-D CT and 2-D flat images of mouse via affine transformation

Zheng Xia, Xishi Huang, Xiaobo Zhou, Youxian Sun, Vasilis Ntziachristos, Stephen T C Wong

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

20 Scopus citations

Abstract

It is difficult to directly coregister the 3-D fluorescence molecular tomography (FMT) image of a small tumor in a mouse whose maximal diameter is only a few millimeters with a larger CT image of the entire animal that spans about 10 cm. This paper proposes a new method to register 2-D flat and 3-D CT image first to facilitate the registration between small 3-D FMT images and large 3-D CT images. A novel algorithm combining differential evolution and improved simplex method for the registration between the 2-D flat and 3-D CT images is introduced and validated with simulated images and real images of mice. The visualization of the alignment of the 3-D FMT and CT image through 2-D registration shows promising results.

Original language	English (US)
Pages (from-to)	569-578
Number of pages	10
Journal	IEEE Transactions on Information Technology in Biomedicine
Volume	12
Issue number	5
DOIs	https://doi.org/10.1109/TITB.2007.904631
State	Published - 2008

Keywords

Animal molecular imaging
Fluorescence molecular (FMT)
Registration
Snake model

ASJC Scopus subject areas

Health Informatics
Health Information Management
Information Systems
Computer Science Applications
Computational Theory and Mathematics
General Medicine

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10.1109/TITB.2007.904631

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title = "Registration of 3-D CT and 2-D flat images of mouse via affine transformation",

abstract = "It is difficult to directly coregister the 3-D fluorescence molecular tomography (FMT) image of a small tumor in a mouse whose maximal diameter is only a few millimeters with a larger CT image of the entire animal that spans about 10 cm. This paper proposes a new method to register 2-D flat and 3-D CT image first to facilitate the registration between small 3-D FMT images and large 3-D CT images. A novel algorithm combining differential evolution and improved simplex method for the registration between the 2-D flat and 3-D CT images is introduced and validated with simulated images and real images of mice. The visualization of the alignment of the 3-D FMT and CT image through 2-D registration shows promising results.",

keywords = "Animal molecular imaging, Fluorescence molecular (FMT), Registration, Snake model",

author = "Zheng Xia and Xishi Huang and Xiaobo Zhou and Youxian Sun and Vasilis Ntziachristos and Wong, {Stephen T C}",

note = "Funding Information: Manuscript received September 24, 2006; revised January 21, 2007 and April 16, 2007. First published June 10, 2008; current version published September 4, 2008. The work of Z. Xia and Y. Sun was supported in part by the Key Technologies R&D Program of Zhejiang Province under Grant 2005C21087, and in part by the Academician Foundation of Zhejiang Province under Grant 2005A1001-13. The work of X. Zhou was supported in part by the Harvard Center for Neurodegeneration and Repair (HCNR) Center for Bioinformatics Research, Harvard Medical School under a Research Grant. The work of S. T. C. Wong was supported in part by the Harvard Center for Neurodegeneration and Repair (HCNR) Center for Bioinformatics Research, Harvard Medical School under a Research Grant, and in part by the National Institutes of Health under Grant R01 LM008696.",

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doi = "10.1109/TITB.2007.904631",

language = "English (US)",

volume = "12",

pages = "569--578",

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AU - Wong, Stephen T C

N1 - Funding Information: Manuscript received September 24, 2006; revised January 21, 2007 and April 16, 2007. First published June 10, 2008; current version published September 4, 2008. The work of Z. Xia and Y. Sun was supported in part by the Key Technologies R&D Program of Zhejiang Province under Grant 2005C21087, and in part by the Academician Foundation of Zhejiang Province under Grant 2005A1001-13. The work of X. Zhou was supported in part by the Harvard Center for Neurodegeneration and Repair (HCNR) Center for Bioinformatics Research, Harvard Medical School under a Research Grant. The work of S. T. C. Wong was supported in part by the Harvard Center for Neurodegeneration and Repair (HCNR) Center for Bioinformatics Research, Harvard Medical School under a Research Grant, and in part by the National Institutes of Health under Grant R01 LM008696.

PY - 2008

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N2 - It is difficult to directly coregister the 3-D fluorescence molecular tomography (FMT) image of a small tumor in a mouse whose maximal diameter is only a few millimeters with a larger CT image of the entire animal that spans about 10 cm. This paper proposes a new method to register 2-D flat and 3-D CT image first to facilitate the registration between small 3-D FMT images and large 3-D CT images. A novel algorithm combining differential evolution and improved simplex method for the registration between the 2-D flat and 3-D CT images is introduced and validated with simulated images and real images of mice. The visualization of the alignment of the 3-D FMT and CT image through 2-D registration shows promising results.

AB - It is difficult to directly coregister the 3-D fluorescence molecular tomography (FMT) image of a small tumor in a mouse whose maximal diameter is only a few millimeters with a larger CT image of the entire animal that spans about 10 cm. This paper proposes a new method to register 2-D flat and 3-D CT image first to facilitate the registration between small 3-D FMT images and large 3-D CT images. A novel algorithm combining differential evolution and improved simplex method for the registration between the 2-D flat and 3-D CT images is introduced and validated with simulated images and real images of mice. The visualization of the alignment of the 3-D FMT and CT image through 2-D registration shows promising results.

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Registration of 3-D CT and 2-D flat images of mouse via affine transformation

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Keywords

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