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Extension of deformable models: Hybrid approaches for analysis of medical images

Ourselin, S; Li, RX; (2005) Extension of deformable models: Hybrid approaches for analysis of medical images. In: 2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-7. (pp. 7182 - 7185). IEEE

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Abstract

Despite deformable models' wide applicability in medical image segmentation, they are sometimes not adequate by themselves to achieve a desired degree of automation, a guaranteed level of accuracy, or an outcome beyond segmentation. In such situations, other methods may be combined with a deformable model to extend its abilities, overcome its shortcomings or increase the assurance of the segmentation accuracy. As examples of such combinations, we discuss the use of deformable models in hybrid approaches, to obtain curvilinear models of tubular structures, patient specific models of the abdominal aortic vessel system, and tissue models for radiation simulation.

Type:Proceedings paper
Title:Extension of deformable models: Hybrid approaches for analysis of medical images
Event:27th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society
Location:Shanghai, PEOPLES R CHINA
Dates:2005-08-31 - 2005-09-03
ISBN:0-7803-8740-6
Keywords:FRONT PROPAGATION
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Medical Physics and Bioengineering

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