Editorial:
Ieee - The Institute Of Electrical And Electronics Engineers, Inc
Fecha de edición:
2012
Cita:
Proceedings of the 2012 10th IEEE International Symposium on Parallel and Distributed Processing with Applications: 10-13 July 2012. Madrid, Spain (2012). IEEE, 867-868.
ISBN:
978-0-7695-4701-5
Agradecimientos:
This work has been partially funded by AMIT Project CDTI CENIT, TEC2007-64731, TEC2008-06715-C02-01, RD07/0014/2009, TRA2009 0175, RECAVA-RETIC, RD09/0077/00087 (Ministerio de Ciencia e Innovacion), ARTEMIS S2009/DPI-1802 (Comunidad de Madrid), and TIN2010-16497 (Ministerio de Ciencia e Innovacion).
Proyecto:
Comunidad de Madrid. S2009/DPI-1802/ARTEMIS Gobierno de España. TIN2010-16497 Gobierno de España. TEC2007-64731 Gobierno de España. TEC2008-06715-C02-01 Gobierno de España. RD07/0014/2009 Gobierno de España. TRA2009 0175 Gobierno de España. RD09/0077/00087
Palabras clave:
X-ray microscopy
,
Computerised tomography
,
Geometry
,
Graphics processing units
,
Image reconstruction
,
Medical image processing
,
Multiprocessing systems
,
Parallel processing
Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proMost small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. Currently there are a strong need to speed-up the reconstruction of XRay CT data in order to extend its clinical applications. We present an efficient modular implementation of an FDK-based reconstruction algorithm that takes advantage of the parallel computing capabilities and the efficient bilinear interpolation provided by general purpose graphic processing units (GPGPU). The proposed implementation of the algorithm is evaluated for a high-resolution micro-CT and achieves a speed-up of 46, while preserving the reconstructed image quali[+][-]
Nota:
Proceedings of: 2012 10 th IEEE International Symposium on Parallel and Distributes Processing with Applicatioons (ISPA 2012). Leganés, Madrid, 10-13 July 2012.
