Breast Image Registration by Combining Finite Elements and Free-Form Deformations

During breast cancer diagnosis, the breasts undergo large deformations due to gravity or compression loads It is therefore non-trivial to recover the deformation and register medical images of the breast in different orientations (e.g prone versus supine) Free-form deformations and biomechanical finite element models have been used to non-rigidly register breast images from prone to supine, but with limited success In this paper, we demonstrate that the use of a finite element model to predict the deformation of the breast from prone to supine provides a significantly more accurate registration compared to free-form deformation methods We also show that the use of this biomechanical model prediction as a prior to free-form deformation provides a significantly more accurate match than does the use of either method independently.

[1]  Gabor Fichtinger,et al.  Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008, 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I , 2008, International Conference on Medical Image Computing and Computer-Assisted Intervention.

[2]  Karol Miller,et al.  Computational Biomechanics for Medicine , 2010 .

[3]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[4]  Radhika Sivaramakrishna,et al.  Breast image registration techniques: a survey , 2006, Medical and Biological Engineering and Computing.

[5]  Vijay Rajagopal,et al.  Creating individual-specific biomechanical models of the breast for medical image analysis. , 2008, Academic radiology.

[6]  David J. Hawkes,et al.  MR Navigated Breast Surgery: Method and Initial Clinical Experience , 2008, MICCAI.

[7]  Vijay Rajagopal,et al.  Modeling breast biomechanics for multi‐modal image analysis—successes and challenges , 2010, Wiley interdisciplinary reviews. Systems biology and medicine.

[8]  Daniel Rueckert,et al.  Volume and Shape Preservation of Enhancing Lesions when Applying Non-rigid Registration to a Time Series of Contrast Enhancing MR Breast Images , 2000, MICCAI.

[9]  Jay B. West,et al.  The distribution of target registration error in rigid-body point-based registration , 2001, IEEE Transactions on Medical Imaging.

[10]  Branislav Jaramaz,et al.  Medical Image Computing and Computer-Assisted Intervention – MICCAI 2000 , 2000, Lecture Notes in Computer Science.

[11]  Martyn P. Nash,et al.  Method for Validating Breast Compression Models Using Normalised Cross-Correlation , 2010 .