High Performance Deformable Image Registration Algorithms for Manycore Processors

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9780124077416: High Performance Deformable Image Registration Algorithms for Manycore Processors

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 algorithms
  • How 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

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
Published by ELSEVIER SCIENCE TECHNOLOGY, United States (2013)
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Book Description ELSEVIER SCIENCE TECHNOLOGY, United States, 2013. Paperback. Book Condition: New. 226 x 150 mm. Language: English . Brand New Book. 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. * Demonstrates how to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithms* Shows how to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs* Provides Programming tricks that can help readers develop other image processing algorithms, including registration algorithms for the GPU. Bookseller Inventory # AA59780124077416

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
Published by ELSEVIER SCIENCE TECHNOLOGY, United States (2013)
ISBN 10: 0124077412 ISBN 13: 9780124077416
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Book Description ELSEVIER SCIENCE TECHNOLOGY, United States, 2013. Paperback. Book Condition: New. 226 x 150 mm. Language: English . Brand New Book. 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. * Demonstrates how to redesign widely used image registration algorithms so as to best expose the underlying parallelism available in these algorithms* Shows how to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs* Provides Programming tricks that can help readers develop other image processing algorithms, including registration algorithms for the GPU. Bookseller Inventory # AA59780124077416

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
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Book Description Morgan Kaufmann Pub, 2013. Paperback. Book Condition: Brand New. 114 pages. 9.00x6.25x0.50 inches. In Stock. Bookseller Inventory # __0124077412

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
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Book Description Elsevier Science & Technology. Paperback. Book Condition: new. BRAND NEW, High Performance Deformable Image Registration Algorithms for Manycore Processors, James Shackleford, Nagarajan Kandasamy, Gregory Sharp, 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 algorithms; how to pose and implement the parallel versions of the algorithms within the single instruction, multiple data (SIMD) model supported by GPUs; and programming "tricks" that can help readers develop other image processing algorithms, including registration algorithms for the GPU. Bookseller Inventory # B9780124077416

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
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Book Description Morgan Kaufmann, 2013. Paperback. Book Condition: NEW. 9780124077416 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Bookseller Inventory # HTANDREE0894074

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
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Book Description Morgan Kaufmann, 2013. Paperback. Book Condition: NEW. 9780124077416 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Bookseller Inventory # HTANDREE01197999

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Shackleford, James; Kandasamy, Nagarajan; Sharp, Gregory
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Book Description Morgan Kaufmann, 2013. Paperback. Book Condition: New. book. Bookseller Inventory # 0124077412

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