Optimization Techniques for Semi-Automated 3D Rigid Registration in Multimodal Image-Guided Deep Brain Stimulation Article Swipe
Fadil Al-Jaberi
,
Melanie Fachet
,
Matthias Moeskes
,
Martin Skalej
,
Christoph Hoeschen
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1515/cdbme-2023-1089
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1515/cdbme-2023-1089
Multimodal image registration is vital in Deep Brain Stimulation (DBS) surgery. DBS treats movement disorders by implanting a neurostimulator device in the brain to deliver electrical impulses. Image registration between computed tomography (CT) and cone beam computed tomography (CBCT) involves fusing images with a specific field of view (FOV) to visualize individual electrode contacts. This contains important information about the location of segmented contacts that can reduce the time required for electrode programming. We performed a semi-automated multimodal image registration with different FOV between CT and CBCT images due to the tiny structures of segmented electrode contacts that necessitate high accuracy in the registration. In this work, we present an optimization workflow for multi-modal image registration using a combination of different similarity metrics, interpolators, and optimizers. Optimization-based rigid image registration (RIR) is a common method for registering images. The selection of appropriate interpolators and similarity metrics is crucial for the success of this optimization-based image registration process.We rely on quantitative measures to compare their performance. Registration was performed on CT and CBCT images for DBS datasets with an image registration algorithm written in Python using the Insight Segmentation and Registration Toolkit (ITK). Several combinations of similarity metrics and interpolators were used, including mean square difference (MSD), mutual information (MI), correlation and nearest neighbors (NN), linear (LI), and B-Spline (SPI), respectively. The combination of a correlation as similarity metric, B-Spline interpolation, and GD optimizer performs the best in optimizing the 3D RIR algorithm, enhancing the visualization of segmented electrode contacts. Patients undergoing DBS therapy may ultimately benefit from this.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1515/cdbme-2023-1089
- https://www.degruyter.com/document/doi/10.1515/cdbme-2023-1089/pdf
- OA Status
- gold
- Cited By
- 3
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386925203
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386925203Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1515/cdbme-2023-1089Digital Object Identifier
- Title
-
Optimization Techniques for Semi-Automated 3D Rigid Registration in Multimodal Image-Guided Deep Brain StimulationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-01Full publication date if available
- Authors
-
Fadil Al-Jaberi, Melanie Fachet, Matthias Moeskes, Martin Skalej, Christoph HoeschenList of authors in order
- Landing page
-
https://doi.org/10.1515/cdbme-2023-1089Publisher landing page
- PDF URL
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https://www.degruyter.com/document/doi/10.1515/cdbme-2023-1089/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://www.degruyter.com/document/doi/10.1515/cdbme-2023-1089/pdfDirect OA link when available
- Concepts
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Image registration, Artificial intelligence, Computer science, Computer vision, Mutual information, Similarity (geometry), Metric (unit), Visualization, Pattern recognition (psychology), Image (mathematics), Economics, Operations managementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2025: 1, 2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| primary_location.landing_page_url | https://doi.org/10.1515/cdbme-2023-1089 |
| publication_date | 2023-09-01 |
| publication_year | 2023 |
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