A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use.
Two-dimensional (2-D)-to-three-dimensional (3-D) registration can improve visualization which may aid minimally invasive neurointerventions. Using clinical and phantom studies, two state-of-the-art approaches to rigid registration are compared quantitatively: an intensity-based algorithm using the g...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2005
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| _version_ | 1797100069728550912 |
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| author | McLaughlin, R Hipwell, J Hawkes, D Noble, J Byrne, J Cox, T |
| author_facet | McLaughlin, R Hipwell, J Hawkes, D Noble, J Byrne, J Cox, T |
| author_sort | McLaughlin, R |
| collection | OXFORD |
| description | Two-dimensional (2-D)-to-three-dimensional (3-D) registration can improve visualization which may aid minimally invasive neurointerventions. Using clinical and phantom studies, two state-of-the-art approaches to rigid registration are compared quantitatively: an intensity-based algorithm using the gradient difference similarity measure; and an iterative closest point (ICP)-based algorithm. The gradient difference approach was found to be more accurate, with an average registration accuracy of 1.7 mm for clinical data, compared to the ICP-based algorithm with an average accuracy of 2.8 mm. In phantom studies, the ICP-based algorithm proved more reliable, but with more complicated clinical data, the gradient difference algorithm was more robust. Average computation time for the ICP-based algorithm was 20 s per registration, compared with 14 min and 50 s for the gradient difference algorithm. |
| first_indexed | 2024-03-07T05:32:33Z |
| format | Journal article |
| id | oxford-uuid:e2c4efd6-69c2-4b5a-97af-b0d7e2a50e58 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:32:33Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | oxford-uuid:e2c4efd6-69c2-4b5a-97af-b0d7e2a50e582022-03-27T10:03:55ZA comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e2c4efd6-69c2-4b5a-97af-b0d7e2a50e58EnglishSymplectic Elements at Oxford2005McLaughlin, RHipwell, JHawkes, DNoble, JByrne, JCox, TTwo-dimensional (2-D)-to-three-dimensional (3-D) registration can improve visualization which may aid minimally invasive neurointerventions. Using clinical and phantom studies, two state-of-the-art approaches to rigid registration are compared quantitatively: an intensity-based algorithm using the gradient difference similarity measure; and an iterative closest point (ICP)-based algorithm. The gradient difference approach was found to be more accurate, with an average registration accuracy of 1.7 mm for clinical data, compared to the ICP-based algorithm with an average accuracy of 2.8 mm. In phantom studies, the ICP-based algorithm proved more reliable, but with more complicated clinical data, the gradient difference algorithm was more robust. Average computation time for the ICP-based algorithm was 20 s per registration, compared with 14 min and 50 s for the gradient difference algorithm. |
| spellingShingle | McLaughlin, R Hipwell, J Hawkes, D Noble, J Byrne, J Cox, T A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. |
| title | A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. |
| title_full | A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. |
| title_fullStr | A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. |
| title_full_unstemmed | A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. |
| title_short | A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. |
| title_sort | comparison of a similarity based and a feature based 2 d 3 d registration method for neurointerventional use |
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