Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients
This paper describes a framework for learning a statistical model of non-rigid deformations induced by interventional procedures. We make use of this learned model to perform constrained non-rigid registration of pre-procedural and post-procedural imaging. We demonstrate results applying this framew...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2016-01-01
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| Series: | NeuroImage: Clinical |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158215300401 |
| _version_ | 1818933162915397632 |
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| author | John A. Onofrey Lawrence H. Staib Xenophon Papademetris |
| author_facet | John A. Onofrey Lawrence H. Staib Xenophon Papademetris |
| author_sort | John A. Onofrey |
| collection | DOAJ |
| description | This paper describes a framework for learning a statistical model of non-rigid deformations induced by interventional procedures. We make use of this learned model to perform constrained non-rigid registration of pre-procedural and post-procedural imaging. We demonstrate results applying this framework to non-rigidly register post-surgical computed tomography (CT) brain images to pre-surgical magnetic resonance images (MRIs) of epilepsy patients who had intra-cranial electroencephalography electrodes surgically implanted. Deformations caused by this surgical procedure, imaging artifacts caused by the electrodes, and the use of multi-modal imaging data make non-rigid registration challenging. Our results show that the use of our proposed framework to constrain the non-rigid registration process results in significantly improved and more robust registration performance compared to using standard rigid and non-rigid registration methods. |
| first_indexed | 2024-12-20T04:44:00Z |
| format | Article |
| id | doaj.art-83d1c82b385841d9ac2980f0f07c4b81 |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-12-20T04:44:00Z |
| publishDate | 2016-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-83d1c82b385841d9ac2980f0f07c4b812022-12-21T19:53:03ZengElsevierNeuroImage: Clinical2213-15822016-01-0110C29130110.1016/j.nicl.2015.12.001Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patientsJohn A. Onofrey0Lawrence H. Staib1Xenophon Papademetris2Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USADepartment of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USADepartment of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USAThis paper describes a framework for learning a statistical model of non-rigid deformations induced by interventional procedures. We make use of this learned model to perform constrained non-rigid registration of pre-procedural and post-procedural imaging. We demonstrate results applying this framework to non-rigidly register post-surgical computed tomography (CT) brain images to pre-surgical magnetic resonance images (MRIs) of epilepsy patients who had intra-cranial electroencephalography electrodes surgically implanted. Deformations caused by this surgical procedure, imaging artifacts caused by the electrodes, and the use of multi-modal imaging data make non-rigid registration challenging. Our results show that the use of our proposed framework to constrain the non-rigid registration process results in significantly improved and more robust registration performance compared to using standard rigid and non-rigid registration methods.http://www.sciencedirect.com/science/article/pii/S2213158215300401Non-rigid registrationStatistical deformation modelSurgical navigationMagnetic resonance imaging (MRI)Computed tomography (CT)Epilepsy |
| spellingShingle | John A. Onofrey Lawrence H. Staib Xenophon Papademetris Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients NeuroImage: Clinical Non-rigid registration Statistical deformation model Surgical navigation Magnetic resonance imaging (MRI) Computed tomography (CT) Epilepsy |
| title | Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients |
| title_full | Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients |
| title_fullStr | Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients |
| title_full_unstemmed | Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients |
| title_short | Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients |
| title_sort | learning intervention induced deformations for non rigid mr ct registration and electrode localization in epilepsy patients |
| topic | Non-rigid registration Statistical deformation model Surgical navigation Magnetic resonance imaging (MRI) Computed tomography (CT) Epilepsy |
| url | http://www.sciencedirect.com/science/article/pii/S2213158215300401 |
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