High performance deformable image registration algorithms for manycore processors:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Waltham, MA
Morgan Kaufmann
2013
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| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans. This book demonstrates: How to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithmsHow to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs Programming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU. Includes bibliographical references |
| Beschreibung: | 1 Online-Ressource (1 online resource) |
| ISBN: | 9780124077416 0124077412 9780124078802 012407880X |
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| 500 | |a High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans. This book demonstrates: How to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithmsHow to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs Programming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU. | ||
| 500 | |a Includes bibliographical references | ||
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| discipline | Informatik |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:18:10Z |
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| isbn | 9780124077416 0124077412 9780124078802 012407880X |
| language | English |
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| spelling | Shackleford, James Verfasser aut High performance deformable image registration algorithms for manycore processors James Shackleford, Nagarajan Kandasamy, Gregory Sharp Waltham, MA Morgan Kaufmann 2013 1 Online-Ressource (1 online resource) txt rdacontent c rdamedia cr rdacarrier High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly data-parallel image registration algorithms suitable for use on modern multi-core architectures, including graphics processing units (GPUs). Focusing on deformable registration, we show how to develop data-parallel versions of the registration algorithm suitable for execution on the GPU. Image registration is the process of aligning two or more images into a common coordinate frame and is a fundamental step to be able to compare or fuse data obtained from different sensor measurements. Extracting useful information from 2D/3D data is essential to realizing key technologies underlying our daily lives. Examples include autonomous vehicles and humanoid robots that can recognize and manipulate objects in cluttered environments using stereo vision and laser sensing and medical imaging to localize and diagnose tumors in internal organs using data captured by CT/MRI scans. This book demonstrates: How to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithmsHow to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs Programming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU. Includes bibliographical references Multiprogramming (Electronic computers) local Computer algorithms local High performance computing local Multiprogramming (Electronic computers) Electronic books Kandasamy, Nagarajan Sonstige oth Sharp, Gregory Sonstige oth http://www.sciencedirect.com/science/book/9780124077416 Verlag Volltext |
| spellingShingle | Shackleford, James High performance deformable image registration algorithms for manycore processors Multiprogramming (Electronic computers) local Computer algorithms local High performance computing local Multiprogramming (Electronic computers) |
| title | High performance deformable image registration algorithms for manycore processors |
| title_auth | High performance deformable image registration algorithms for manycore processors |
| title_exact_search | High performance deformable image registration algorithms for manycore processors |
| title_full | High performance deformable image registration algorithms for manycore processors James Shackleford, Nagarajan Kandasamy, Gregory Sharp |
| title_fullStr | High performance deformable image registration algorithms for manycore processors James Shackleford, Nagarajan Kandasamy, Gregory Sharp |
| title_full_unstemmed | High performance deformable image registration algorithms for manycore processors James Shackleford, Nagarajan Kandasamy, Gregory Sharp |
| title_short | High performance deformable image registration algorithms for manycore processors |
| title_sort | high performance deformable image registration algorithms for manycore processors |
| topic | Multiprogramming (Electronic computers) local Computer algorithms local High performance computing local Multiprogramming (Electronic computers) |
| topic_facet | Multiprogramming (Electronic computers) Computer algorithms High performance computing |
| url | http://www.sciencedirect.com/science/book/9780124077416 |
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