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Proceedings Paper

Finite-element deformable sheet-curve models for registration of breast MR images
Author(s): Jianhua Xuan; Matthew T. Freedman; Yue Joseph Wang
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Paper Abstract

It is clinically important to develop novel approaches to accurately assess early response to chemoprevention. We propose to quantitatively measure changes of breast density and breast vascularity in glandular tissue to assess early response to chemoprevention. In order to accurately extract glandular tissue using pre- and post-contrast magnetic resonance (MR) images, non-rigid registration is the key to align MR images by recovering the local deformations. In this paper, a new registration method has been developed using finite-element deformable sheet-curve models to accurately register MR breast images for extraction of glandular tissue. Finite-element deformable sheet-curve models are coupling dynamic systems to physically model the boundary deformation and image deformation. Specifically, deformable curves are used to obtain a reliable matching of the boundaries using physically constrained deformations. A deformable sheet with the energy functional of thin-plate-splines is used to model complex local deformations between the MR breast images. Finite-element deformable sheet-curve models have been applied to register both digital phantoms and MR breast image. The experimental results have been compared to point-based methods such as the thin-plate-spline (TPS) approach, which demonstrates that our method is of a great improvement over point-based registration methods in both boundary alignment and local deformation recovery.

Paper Details

Date Published: 15 May 2003
PDF: 12 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480859
Show Author Affiliations
Jianhua Xuan, Catholic Univ. of America (United States)
Matthew T. Freedman, Georgetown Univ. Medical Ctr. (United States)
Yue Joseph Wang, Catholic Univ. of America (United States)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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