This paper describes the development of a cylindrical affine transformation model for image registration. The
usefulness of the model for initial alignment was demonstrated for the application of registering prone and
supine 3D MR images of the breast. Final registration results visually improved when using the cylindrical affine
transformation model instead of none or a Cartesian affine transformation model before non-rigid registration.
We have previously proposed a system for image-guided breast surgery that compensates for the deformation of the
breast during patient set-up. Since breast surgery is performed with the patient positioned supine, but MR imaging is
performed with the patient positioned prone, a large soft tissue deformation must be accounted for. A biomechanical
model can help to constrain the associated registrations. However the necessary material properties for breast tissue
under such strains are not available in the literature. This paper describes a method to determine these properties. We
first show that the stress-free or 'reference' state of an object can be approximated by submerging it in liquid of a similar
density. MR images of the breast submerged in water and in a pendulous prone position are acquired. An intensity-based
non-rigid image registration algorithm is used to establish point-by-point correspondence between these images. A finite
element model of the breast is then constructed from the submerged images and the deformation to free-pendulous is
simulated. The material properties for which the model deformation best fits the observed deformation are determined.
Assuming neo-Hookean material properties, the initial shear moduli of fibroglandular and adipose tissue are found to be
0.4 kPa and 0.3 kPa respectively.