Name
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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1117/12.769945 | PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) |
Keywords | Field | DocType |
image-based finite element models of physiology,breast modelling,individual-specific model generation,medical image-based biomechanical model of the breast,analysis of soft tissue deformation | Data point,Biomedical engineering,Computer vision,Mammography,Reference model,Breast cancer,Finite element method,Artificial intelligence,Palpation,Engineering,Image registration,Magnetic resonance imaging | Conference |
Volume | ISSN | Citations |
6918 | 0277-786X | 1 |
PageRank | References | Authors |
0.37 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angela Lee | 1 | 8 | 1.31 |
| Vijay Rajagopal | 2 | 47 | 6.87 |
| jaehoon chung | 3 | 1 | 0.37 |
| peter bier | 4 | 1 | 0.37 |
| Poul M. F. Nielsen | 5 | 328 | 29.20 |
| Martyn P. Nash | 6 | 133 | 23.64 |