Back to Search
Start Over
Groupwise Multimodal Image Registration Using Joint Total Variation
- Source :
- Communications in Computer and Information Science ISBN: 9783030527907, MIUA
- Publication Year :
- 2020
- Publisher :
- Springer International Publishing, 2020.
-
Abstract
- In medical imaging it is common practice to acquire a wide range of modalities (MRI, CT, PET, etc.), to highlight different structures or pathologies. As patient movement between scans or scanning session is unavoidable, registration is often an essential step before any subsequent image analysis. In this paper, we introduce a cost function based on joint total variation for such multimodal image registration. This cost function has the advantage of enabling principled, groupwise alignment of multiple images, whilst being insensitive to strong intensity non-uniformities. We evaluate our algorithm on rigidly aligning both simulated and real 3D brain scans. This validation shows robustness to strong intensity non-uniformities and low registration errors for CT/PET to MRI alignment. Our implementation is publicly available at https://github.com/brudfors/coregistration-njtv.
- Subjects :
- Modalities
business.industry
Computer science
02 engineering and technology
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Neuroimaging
Robustness (computer science)
Multimodal image
0202 electrical engineering, electronic engineering, information engineering
Medical imaging
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
business
Subjects
Details
- ISBN :
- 978-3-030-52790-7
- ISBNs :
- 9783030527907
- Database :
- OpenAIRE
- Journal :
- Communications in Computer and Information Science ISBN: 9783030527907, MIUA
- Accession number :
- edsair.doi...........342c88a98ed293f741fec1f6eafbfa97
- Full Text :
- https://doi.org/10.1007/978-3-030-52791-4_15