| Comparing two approaches to rigid registration of three-dimensional ultrasound and magnetic resonance images for neurosurgery. | |
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MedLine Citation:
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PMID: 21633799 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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PURPOSE: We present a new technique for registering magnetic resonance (MR) and ultrasound images in the context of neurosurgery. It involves generating a pseudo-ultrasound (pseudo-US) from a segmented MR image and uses cross-correlation as the cost function to register the pseudo-US to the real ultrasound data. The algorithm's performance is compared with that of a state-of-the-art technique that uses a median-filtered MR image to register to a Gaussian-blurred ultrasound using a normalized mutual information (NMI) objective function. METHODS: The two methods were tested on data from 15 patients with brain tumor, including low-and high-grade gliomas, in both first operations and reoperations. Two metrics were used to evaluate registration accuracy: (1) the mean distance between corresponding points, identified on both MR and ultrasound images by two experts, and (2) ratings based on visual comparison by one neurosurgeon. RESULTS: The mean residual distance of the pseudo-US technique, 2.97 mm, is significantly more accurate (p = .0011) than that of the NMI approach, 4.86 mm. The visual assessment shows that only 4 of the 15 cases had a satisfactory initial alignment based on homologous skin-point registration. There is a significant correlation between the quantitative distance measures and the qualitative ratings (rho = 0.785). CONCLUSION: The results show that the pseudo-US rigid registration technique robustly improves the MRI-ultrasound alignment when compared with the initial alignment, even when applied to highly distorted brains and a large range of tumor sizes and appearances. |
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Authors:
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Laurence Mercier; Vladimir Fonov; Claire Haegelen; Rolando F Del Maestro; Kevin Petrecca; D Louis Collins |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-6-2 |
Journal Detail:
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Title: International journal of computer assisted radiology and surgery Volume: - ISSN: 1861-6429 ISO Abbreviation: - Publication Date: 2011 Jun |
Date Detail:
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Created Date: 2011-6-2 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101499225 Medline TA: Int J Comput Assist Radiol Surg Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Room WB-320, 3801 University Street, Montreal, QC, H3A 2B4, Canada, laurence@bic.mni.mcgill.ca. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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