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Proceedings Paper

Biomechanical modelling for breast image registration
Author(s): Angela Lee; Vijay Rajagopal; Jae-Hoon Chung; Peter Bier; Poul M. F. Nielsen; Martyn P. Nash
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Paper Abstract

Breast cancer is a leading cause of death in women. Tumours are usually detected by palpation or X-ray mammography followed by further imaging, such as magnetic resonance imaging (MRI) or ultrasound. The aim of this research is to develop a biophysically-based computational tool that will allow accurate collocation of features (such as suspicious lesions) across multiple imaging views and modalities in order to improve clinicians' diagnosis of breast cancer. We have developed a computational framework for generating individual-specific, 3D finite element models of the breast. MR images were obtained of the breast under gravity loading and neutrally buoyant conditions. Neutrally buoyant breast images, obtained whilst immersing the breast in water, were used to estimate the unloaded geometry of the breast (for present purposes, we have assumed that the densities of water and breast tissue are equal). These images were segmented to isolate the breast tissues, and a tricubic Hermite finite element mesh was fitted to the digitised data points in order to produce a customized breast model. The model was deformed, in accordance with finite deformation elasticity theory, to predict the gravity loaded state of the breast in the prone position. The unloaded breast images were embedded into the reference model and warped based on the predicted deformation. In order to analyse the accuracy of the model predictions, the cross-correlation image comparison metric was used to compare the warped, resampled images with the clinical images of the prone gravity loaded state. We believe that a biomechanical image registration tool of this kind will aid radiologists to provide more reliable diagnosis and localisation of breast cancer.

Paper Details

Date Published: 17 March 2008
PDF: 8 pages
Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69180U (17 March 2008); doi: 10.1117/12.769945
Show Author Affiliations
Angela Lee, Univ. of Auckland (New Zealand)
Vijay Rajagopal, Univ. of Auckland (New Zealand)
Jae-Hoon Chung, Univ. of Auckland (New Zealand)
Peter Bier, Univ. of Auckland (New Zealand)
Poul M. F. Nielsen, Univ. of Auckland (New Zealand)
Martyn P. Nash, Univ. of Auckland (New Zealand)

Published in SPIE Proceedings Vol. 6918:
Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kevin Robert Cleary, Editor(s)

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