High Performance Deformable Image Registration Algorithms for Manycore Processors

James Shackleford

ISBN 10: 0124077412 / ISBN 13: 9780124077416

Verlag: Elsevier Science & Technology, Morgan Kaufmann, 2013

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -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. Englisch.

Bestandsnummer des Verkäufers 9780124077416

Bibliografische Details

• Titel: High Performance Deformable Image Registration Algorithms for Manycore Processors
• Verlag: Elsevier Science & Technology, Morgan Kaufmann
• Erscheinungsjahr: 2013
• Sprache: Englisch
• ISBN-10: 0124077412
• ISBN-13: 9780124077416
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 229B x 152 H x 6 T Millimeter Breite: 229 mm, Höhe: 152 mm, Tiefe: 6 mm
• Gewicht: 210 Gramm

Über diesen Titel

Inhaltsangabe

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.

Über die Autorin bzw. den Autor

Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.