Ms. Angela W. Lee Profile

Angela W. Lee

at Univ of Auckland

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Proceedings Article | 28 February 2009 Paper

Correlation of breast image alignment using biomechanical modelling

Angela Lee, Vijay Rajagopal, Peter Bier, Poul M. Nielsen, Martyn Nash

Proceedings Volume 7262, 726219 (2009) https://doi.org/10.1117/12.811789

KEYWORDS: Breast, 3D modeling, Tissues, 3D image processing, Data modeling, Head, Magnetic resonance imaging, Mammography, Breast cancer, Modeling

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Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC²) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.

Proceedings Article | 17 March 2008 Paper

Biomechanical modelling for breast image registration

Angela Lee, Vijay Rajagopal, Jae-Hoon Chung, Peter Bier, Poul Nielsen, Martyn Nash

Proceedings Volume 6918, 69180U (2008) https://doi.org/10.1117/12.769945

KEYWORDS: Breast, 3D modeling, Magnetic resonance imaging, Tissues, Image segmentation, 3D image processing, Data modeling, Image registration, Mammography, Modeling

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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.

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