Difference between revisions of "2012 Winter Project Week:PelvicRegistration"
| Line 20: | Line 20: | ||
<h3>Approach, Plan</h3> | <h3>Approach, Plan</h3> | ||
We use a surface based registration algorithm with elastic energy as the | We use a surface based registration algorithm with elastic energy as the | ||
| − | penalty for the deformation. Ultrasound images are collected using a stepper, with fixed slice spacing in the axial view. The object is segmented (contoured) in both MRI and ultrasound images and a surface model is created. Gaussian mapping of the surface reduces the registration problem to finding an appropriate rotation of the coordinate systems that minimizes a cost function. This cost is the elastic energy of deforming the surface from | + | penalty for the deformation. Ultrasound images are collected using a stepper, with fixed slice spacing in the axial view. The object is segmented (contoured) in both MRI and ultrasound images and a surface model is created. Gaussian mapping of the surface reduces the registration problem to finding an appropriate rotation of the coordinate systems that minimizes a cost function. This cost is the elastic energy of deforming the surface from MRI to US sconfiguration. |
| − | + | ||
</div> | </div> | ||
Revision as of 19:33, 21 December 2011
Home < 2012 Winter Project Week:PelvicRegistration
Investigators at Brigham and Women's
- Computational core: Mehdi Moradi, Firdaus Janoos, Tina Kapur, Jan Egger, Sandy Wells
- Clinical core: Clare Tempany, Paul Nguyen
- Prostate core: Andriy Fedorov
- Present team members in SLC: Mehdi Moradi, Andriy Fedorov, Jan Egger.
Objective
We will implement a basic surface-based deformable registration solution to register prostate 3D ultrasound data to MRI. This is to enable clinical integration of the diagnostic MRI data with ultrasound during prostate brachytherapy with dynamic intraoperative dose planning.
Approach, Plan
We use a surface based registration algorithm with elastic energy as the penalty for the deformation. Ultrasound images are collected using a stepper, with fixed slice spacing in the axial view. The object is segmented (contoured) in both MRI and ultrasound images and a surface model is created. Gaussian mapping of the surface reduces the registration problem to finding an appropriate rotation of the coordinate systems that minimizes a cost function. This cost is the elastic energy of deforming the surface from MRI to US sconfiguration.
