Mesh Processing in Medical Image Analysis 2012: MICCAI 2012 by Noura Faraj, Jean-Marc Thiery, Isabelle Bloch, Nadège

Mesh Processing in Medical Image Analysis 2012: MICCAI 2012 by Noura Faraj, Jean-Marc Thiery, Isabelle Bloch, Nadège

By Noura Faraj, Jean-Marc Thiery, Isabelle Bloch, Nadège Varsier, Joe Wiart (auth.), Joshua A. Levine, Rasmus R. Paulsen, Yongjie Zhang (eds.)

This e-book constitutes the refereed court cases of the foreign Workshop on Mesh Processing in clinical picture research, MeshMed 2012, held in great, France, in October 2012 along with MICCAI 2012, the fifteenth foreign convention on scientific photo Computing and computing device Assisted Intervention. The ebook comprises sixteen submissions, eight have been chosen for presentation besides the three plenary talks consultant of the meshing, and eight have been chosen for poster displays. The papers hide a vast diversity of subject matters, together with statistical form research and atlas building, novel meshing methods, gentle tissue simulation, quad dominant meshing and mesh established form descriptors. The defined thoughts have been utilized to quite a few scientific facts together with cortical bones, ear canals, cerebral aneurysms and vascular structures.

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Extra info for Mesh Processing in Medical Image Analysis 2012: MICCAI 2012 International Workshop, MeshMed 2012, Nice, France, October 1, 2012. Proceedings

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Osteoporosis International 7, 113–118 (1997) 20. : Morphometric changes in the heights and anteroposterior diameters of the lumbar intervertebral discs with age. Journal of Anatomy 175, 159–168 (1991) 21. : Age-related variations in the horizontal and vertical diameters of the pedicles of the lumbar spine. Journal of Anatomy 186, 321–328 (1995) 22. : Classification of vertebral fractures. Journal of Bone and Mineral Research 6(3), 207–215 (1991) 23. : Measurements of vertebral shape by radiographic morphometry: sex differences and relationships with vertebral level and lumbar lordosis.

In Sect. 3, we describe how CPM is implemented on the femur mesh. Finally, the placement of the cortical surface meshes is detailed in Sect. 4. 42 J. Zhang et al. (a) (b) Fig. 1. Overview of the proposed method. The generic piecewise-polynomial parametric femur mesh is shown in (a) with node locations in red. The key steps in the meshing process are illustrated in (b). 1 Femoral Surface Mesh We model femoral surfaces using a piecewise-polynomial parametric mesh. The mesh is composed of rectangular and triangular patches, in which the surface is given by K s(ξ1 , ξ2 ) = xi φi (ξ1 , ξ2 ) (1) i=1 where ξ1 and ξ2 are the 2-D patch coordinates, K is the number of nodes in the patch, x = (xx , xy , xz ) are the 3-D coordinates of a patch node, and φ is the quartic Lagrange polynomial basis function associated with a node.

4(b). A profile sampled normal to the outer surface may pass tangentially through the cortex, leading to an unreliable estimate of the inner cortical surface, and thickness. Smoothing penalties applied during inner mesh fitting mitigated this problem to a degree, giving the thick average linea aspera shown in Fig. 3(d), as expected. However, better ground-truth data, and a better definition of cortical thickness where external ridges are present, will be needed to validate the true accuracy. 5 Conclusions and Future Work We have presented a fully automated method for segmenting and modelling femur cortical surfaces from clinical CT images.

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