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Cross-Sim-NGF: FFT-...
Cross-Sim-NGF: FFT-Based Global Rigid Multimodal Alignment of Image Volumes using Normalized Gradient Fields
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- Öfverstedt, Johan (författare)
- Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Uppsala University
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- Lindblad, Joakim (författare)
- Uppsala universitet,Bildanalys och människa-datorinteraktion,Avdelningen för visuell information och interaktion
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- Sladoje, Natasa (författare)
- Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion
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(creator_code:org_t)
- 2021
- Engelska.
- Relaterad länk:
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https://arxiv.org/ab...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Multimodal image alignment involves finding spatial correspondences between volumes varying in appearance and structure. Automated alignment methods are often based on local optimization that can be highly sensitive to their initialization. We propose a global optimization method for rigid multimodal 3D image alignment, based on a novel efficient algorithm for computing similarity of normalized gradient fields (NGF) in the frequency domain. We validate the method experimentally on a dataset comprised of 20 brain volumes acquired in four modalities (T1w, Flair, CT, [18F] FDG PET), synthetically displaced with known transformations. The proposed method exhibits excellent performance on all six possible modality combinations, and outperforms all four reference methods by a large margin. The method is fast; a 3.4Mvoxel global rigid alignment requires approximately 40 seconds of computation, and the proposed algorithm outperforms a direct algorithm for the same task by more than three orders of magnitude. Open-source implementation is provided.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
Nyckelord
- Computerized Image Processing
- Datoriserad bildbehandling
Publikations- och innehållstyp
- vet (ämneskategori)
- ovr (ämneskategori)