High Performance Deformable Image Registration Algorithms for Manycore Processors

Szerző: James Shackleford

Nyelv:

Kötés: Puha kötésű

Kiadó: Elsevier Books

Elérhetőség: Beszállítói készleten

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High Performance Deformable Image Registration Algorithms for Manycore Processors develops highly da...

Információk a könyvről

Szerző

James Shackleford

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2013

oldal

122

EAN

9780124077416

ISBN

0124077412

Enbook ID

01369237

Kiadó

Elsevier Books

Súly

184

Méretek

165 x 229 x 7

Teljes leírás

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.

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High Performance Deformable Image Registration Algorithms for Manycore Processors

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