Difference between revisions of "2012 Winter Project Week:PelvicRegistration"

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We use a surface based registration algorithm with elastic energy as the
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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 pre-operative to intraop configuration.
 
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We use a surface based registration algorithm with elastic energy as the
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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 pre-operative to intraop configuration.
 
 
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Revision as of 19:31, 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 pre-operative to intraop configuration.

Progress