Local and Global Consistency Measures in Intensity-based Medical Image Registration Article Swipe
This thesis investigates local and global structural consistency measures to be used as regularization constraints in intensity-based registration of partial images for field-of-view extension. The proposed measures are employed in cases where the overlap size is small or the amount of shared information is insufficient. We show how the introduced regularization strategies can be effectively used for a consistent registration of partial observations of a scene in several medical applications including microscopy image stitching and histology volume reconstruction.
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Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://mediatum.ub.tum.de/node?id=1232494
- http://mediatum.ub.tum.de/doc/1232494/document.pdf
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2755469767
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2755469767Canonical identifier for this work in OpenAlex
- Title
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Local and Global Consistency Measures in Intensity-based Medical Image RegistrationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-01-01Full publication date if available
- Authors
-
Mehmet YiğitsoyList of authors in order
- Landing page
-
https://mediatum.ub.tum.de/node?id=1232494Publisher landing page
- PDF URL
-
https://mediatum.ub.tum.de/doc/1232494/document.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://mediatum.ub.tum.de/doc/1232494/document.pdfDirect OA link when available
- Concepts
-
Image stitching, Image registration, Computer vision, Artificial intelligence, Regularization (linguistics), Computer science, Consistency (knowledge bases), Mathematics, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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