In this chapter we present a parallel computational method for 3D image segmentation. It is based on a three-dimensional semi-implicit complementary volume numerical scheme for solving the Riemannian mean curvature flowof graphs called the subjective surface method. The parallel method is introduced for massively parallel processor (MPP) architecture using the message passing interface (MPI) standard, so it is suitable, e.g., for clusters of Linux computers. The scheme is applied to segmentation of 3D echocardiographic images.

Mikula K., Sarti A. (2007). Parallel co-volume subjective surface method for 3D medical image segmentation,. BERLIN : Springer Publishers.

Parallel co-volume subjective surface method for 3D medical image segmentation,

SARTI, ALESSANDRO
2007

Abstract

In this chapter we present a parallel computational method for 3D image segmentation. It is based on a three-dimensional semi-implicit complementary volume numerical scheme for solving the Riemannian mean curvature flowof graphs called the subjective surface method. The parallel method is introduced for massively parallel processor (MPP) architecture using the message passing interface (MPI) standard, so it is suitable, e.g., for clusters of Linux computers. The scheme is applied to segmentation of 3D echocardiographic images.
2007
Parametric and Geometric Deformable Models: An application in Biomaterials and Medical Imagery
123
160
Mikula K., Sarti A. (2007). Parallel co-volume subjective surface method for 3D medical image segmentation,. BERLIN : Springer Publishers.
Mikula K.; Sarti A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/59710
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