Level-set methods have proven to be powerful and flexible tools in computer vision and medical imaging. Unfortunately, the flexibility of such models has historically resulted in long computational times and therefore limited clinical utility. In this context, we propose the first rigorous GPU implementation of the sparse field algorithm. We show that this model is able to reach high computational efficiency with no reduction in segmentation accuracy compared to its sequential counter-part.

A rigorous and efficient GPU implementation of level-set sparse field algorithm / Francesca Galluzzo;Nicolo Speciale;Olivier Bernard. - STAMPA. - (2012), pp. 1705-1708. (Intervento presentato al convegno 2012 19th IEEE International Conference on Image Processing (ICIP) tenutosi a Orlando, FL, United States nel 30 September 2012 through 3 October 2012) [10.1109/ICIP.2012.6467207].

A rigorous and efficient GPU implementation of level-set sparse field algorithm

GALLUZZO, FRANCESCA;SPECIALE, NICOLO'ATTILIO;
2012

Abstract

Level-set methods have proven to be powerful and flexible tools in computer vision and medical imaging. Unfortunately, the flexibility of such models has historically resulted in long computational times and therefore limited clinical utility. In this context, we propose the first rigorous GPU implementation of the sparse field algorithm. We show that this model is able to reach high computational efficiency with no reduction in segmentation accuracy compared to its sequential counter-part.
2012
2012 19th IEEE International Conference on Image Processing
1705
1708
A rigorous and efficient GPU implementation of level-set sparse field algorithm / Francesca Galluzzo;Nicolo Speciale;Olivier Bernard. - STAMPA. - (2012), pp. 1705-1708. (Intervento presentato al convegno 2012 19th IEEE International Conference on Image Processing (ICIP) tenutosi a Orlando, FL, United States nel 30 September 2012 through 3 October 2012) [10.1109/ICIP.2012.6467207].
Francesca Galluzzo;Nicolo Speciale;Olivier Bernard
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/396215
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