We describe an algorithm and its implementation details for automatic image-based registration of intra-operative ultrasound to MRI for brain-shift correction during neurosurgery. It is evaluated on a public database of 22 surgeries for retrospective evaluation, with a particular focus on choosing the appropriate transformation model and designing the most meaningful evaluation strategy. The method succeeds in a fully automatic fashion in all cases, with an average landmark registration error for the rigid model of 1.75mm.
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We describe an algorithm and its implementation details for automatic image-based registration of intra-operative ultrasound to MRI for brain-shift correction during neurosurgery. It is evaluated on a public database of 22 surgeries for retrospective evaluation, with a particular focus on choosing the appropriate transformation model and designing the most meaningful evaluation strategy. The method succeeds in a fully automatic fashion in all cases, with an average landmark registration error fo...
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