Accelerating image registration with the Johnson-Lindenstrauss lemma: application to imaging 3-D neural ultrastructure with electron microscopy
| Autor: | Davi D. Bock, Simon K. Warfield, Ayelet Akselrod-Ballin, R. C. Reid |
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| Rok vydání: | 2011 |
| Předmět: |
Johnson–Lindenstrauss lemma
Databases Factual Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image registration Image processing Iterative reconstruction Article law.invention Microscopy Electron Transmission law Microscopy Image Processing Computer-Assisted Animals Computer vision Electrical and Electronic Engineering Projection (set theory) Image resolution Fixation (histology) Radiological and Ultrasound Technology business.industry Histocytochemistry Ferrets Geniculate Bodies Computer Science Applications Transmission electron microscopy Feature (computer vision) Ultrastructure Artificial intelligence Electron microscope business Software Algorithms |
| Zdroj: | IEEE transactions on medical imaging. 30(7) |
| ISSN: | 1558-254X |
| Popis: | We present a novel algorithm to accelerate feature based registration, and demonstrate the utility of the algorithm for the alignment of large transmission electron microscopy (TEM) images to create 3-D images of neural ultrastructure. In contrast to the most similar algorithms, which achieve small computation times by truncated search, our algorithm uses a novel randomized projection to accelerate feature comparison and to enable global search. Further, we demonstrate robust estimation of nonrigid transformations with a novel probabilistic correspondence framework, that enables large TEM images to be rapidly brought into alignment, removing characteristic distortions of the tissue fixation and imaging process. We analyze the impact of randomized projections upon correspondence detection, and upon transformation accuracy, and demonstrate that accuracy is maintained. We provide experimental results that demonstrate significant reduction in computation time and successful alignment of TEM images. |
| Databáze: | OpenAIRE |
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