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The following paper describes a novel approach to a medical image segmentation problem. The fully automated computational procedure receives as input images from CT scan exams of the human femur and returns a three dimensional representation of the bone. This patient specific iterative approach is based in 3D active contours without edges, implemented over a level set framework, on which the evolution of the contour depends on local image parameters which can easily be defined by the user but also on a priori information about the volume to segment. This joint approach will lead to an optimal solution convergence of the iterative method. The resulting point cloud can be an excellent starting point for a Finite Element mesh generation and analysis or the basis for a stereolitography for example. | 101.97 KB | Adobe PDF |
Advisor(s)
Abstract(s)
The following paper describes a novel approach to a medical image segmentation problem. The fully automated computational procedure receives as input images from CT scan exams of the human femur and returns a three dimensional representation of the bone. This patient specific iterative approach is based in 3D active contours without edges, implemented over a level set framework, on which the evolution of the contour depends on local image parameters which can easily be defined by the user but also on a priori information about the volume to segment. This joint approach will lead to an optimal solution convergence of the iterative method. The resulting point cloud can be an excellent starting point for a Finite Element mesh generation and analysis or the basis for a stereolitography for example.
Description
Computational Vision and Medical Image Processing, IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013, Pages 271 - 276, 2014 4th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013, Funchal, 14 October 2013, through 16 October 2014 - Code 166569
Keywords
Bone Finite element method Image processing Image segmentation Iterative methods Medical computing Medical image processing Medical imaging Mesh generation
Pedagogical Context
Citation
D. Almeida, J. Folgado, P.R. Fernandes & R.B. Ruben. 3D shape prior active contours for an automatic segmentation of a patient specific femur from a CT scan. (2013). In Computational Vision and Medical Image Processing IV: VIPIMAGE 2013 (1st ed.). CRC Press. https://doi.org/10.1201/b15810-52.
Publisher
CRC Press
CC License
Without CC licence