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Published in:
2008 | OriginalPaper | Chapter
Evaluation of Brain MRI Alignment with the Robust Hausdorff Distance Measures
Authors : Andriy Fedorov, Eric Billet, Marcel Prastawa, Guido Gerig, Alireza Radmanesh, Simon K. Warfield, Ron Kikinis, Nikos Chrisochoides
Published in: Advances in Visual Computing
Publisher: Springer Berlin Heidelberg
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We present a novel automated method for assessment of image alignment, applied to non-rigid registration of brain Magnetic Resonance Imaging data (MRI) for image-guided neurosurgery. We propose a number of robust modifications to the Hausdorff distance (HD) metric, and apply it to the edges recovered from the brain MRI to evaluate the accuracy of image alignment. The evaluation results on synthetic images, simulated tumor growth MRI and real neurosurgery data with expert-identified anatomical landmarks, confirm that the accuracy of alignment error estimation is improved compared to the conventional HD. The proposed approach can be used to increase confidence in the registration results, assist in registration parameter selection, and provide local estimates and visual assessment of the registration error.