LEADER 00000cam a2200601 a 4500 
001    854997085 
003    OCoLC 
005    20240129213017.0 
006    m     o  d         
007    cr cnu---unuuu 
008    130805s2013    mau     ob    000 0 eng d 
019    857791716 
020    9780124078802 
020    012407880X 
029 1  AU@|b000052005840 
029 1  AU@|b000053295450 
029 1  AU@|b000058064923 
029 1  AU@|b000067102593 
029 1  CHNEW|b001011344 
029 1  DEBBG|bBV041432355 
029 1  DEBBG|bBV042314338 
029 1  DEBSZ|b398282684 
029 1  DEBSZ|b405350058 
029 1  GBVCP|b785371540 
029 1  NZ1|b15193703 
035    (OCoLC)854997085|z(OCoLC)857791716 
037    CL0500000287|bSafari Books Online 
040    OPELS|beng|epn|cOPELS|dYDXCP|dUMI|dCOO|dB24X7|dDEBSZ|dUPM
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       |dOCLCQ|dOCLCO 
049    INap 
082 04 005.2/75 
082 04 005.2/75|223 
099    eBook O’Reilly for Public Libraries 
100 1  Shackleford, James. 
245 10 High performance deformable image registration algorithms 
       for manycore processors /|cJames Shackleford, Nagarajan 
       Kandasamy, Gregory Sharp.|h[O'Reilly electronic resource] 
260    Waltham, MA :|bMorgan Kaufmann,|c2013. 
300    1 online resource 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
504    Includes bibliographical references. 
505 0  Chapter 1. Introduction -- chapter 2. Unimodal B-spline 
       registration -- chapter 3. Multimodal B-spline 
       registration -- chapter 4. Analytic vector field 
       regularization for B-spline parameterized methods -- 
       chapter 5. Deformable registration using optical-flow 
       methods -- chapter 6. Plastimatch -- an open-source 
       software for radiotherapy imaging. 
520    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 
588 0  Online resource; title details screen (Elsevier, viewed 
       August 5, 2013). 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
650  0 Multiprogramming (Electronic computers) 
650  6 Multiprogrammation. 
650  7 Multiprogramming (Electronic computers)|2fast 
700 1  Kandasamy, Nagarajan. 
700 1  Sharp, Gregory. 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/~/9780124077416/?ar
       |zAvailalbe on O'Reilly for Public Libraries 
938    Books 24x7|bB247|nbke00056547 
938    Cengage Learning|bGVRL|nGVRL8CXE 
938    YBP Library Services|bYANK|n10845164 
994    92|bJFN