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Topological Fragmentation of Medical 3D Surface Mesh Models for Multi-Hierarchy Anatomical Classification

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Języki publikacji
EN
Abstrakty
EN
High resolution 3D mesh representations of patient anatomy with appendant functional classification are of high importance in the field of clinical education and therapy planning. Thereby, classification is not always possible directly from patient morphology, thus necessitating tool support. In this work a hierarchical mesh data model for multi-hierarchy anatomical classification is introduced, allowing labeling of a patient model according to various medical taxonomies. The classification regions are thereby specified utilizing a spline representation to be placed and deformed by a medical expert at low effort. Furthermore, application of randomized dilation allows conversion of the specified regions on the surface into fragmented and closed sub-meshes, comprising the entire anatomical structure. As proof of concept, the semi-automated classification method is implemented for VTK library and visualization of the multihierarchy anatomical model is validated with OpenGL, successfully extracting sub-meshes of the brain lobes and preparing classification regions according to Brodmann area taxonomy.
Twórcy
  • Research Group Bio- and Medical Informatics, Department of Research and Development at the University of Applied Sciences Upper Austria, Campus Hagenberg, Softwarepark 11, 4232 Hagenberg, Austria
  • Department of Biomedical Informatics at the University of Applied Sciences Upper Austria, School of Informatics, Communications and Media, Softwarepark 11, 4232 Hagenberg, Austria
Bibliografia
  • [1] A. Pommert, K.-H. Höhne, B. Pflesser, E. Richter, M. Riemer, T. Schiemann, R. Schubert, U. Schumacher and U. Tiede, Creating a highresolution spatial/symbolic model of the inner organs based on the Visible Human, In: R. Haux and C.A. Kulikowski (eds.): Yearbook of Medical Informatics 2003: Quality of Health Care: The Role of Informatics, Stuttgart, Germany: Schattauer, 2003, 530-537.
  • [2] G. Zwettler, W. Backfrieder, R. Swoboda, F. Pfeifer, H. Kratochwill and F. Fellner, Automatic Liver Classification with Multi-Slice CT Data, Proc. of the 1st Forschungsforum der österreichischen Fachhochschulen FFH2007, Salzburg, Austria, 2007, 425-426.
  • [3] C.-Y. Kao, M. Hofer,G. Sapiro, J. Stern and D. Rottenberg, A Geometric Method for Automatic Extraction of Sulcal Fundi, IEEE International Symposium on Biomedical Imaging, 2006, 1168-1171.
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  • [5] W. Schroeder, K. Martin and B. Lorensen, The Visualization Toolkit An Object-Oriented Approach to 3D Graphics, 4th ed., Kitware Inc., 2005.
  • [6] D. Shreiner, The Khronos OpenGL ARB Working Group: OpenGL Programming Guide: The Official Guide to Learning OpenGL, version 4.3, 8th edition, Addison-Wesley, 2013.
  • [7] E.W. Dijkstra, A note on two problems in connexion with graphs, Numerische Mathematik 1, 1959, 269-271.
  • [8] T.M. Liebling, Voronoi Diagrams and Delaunay Triangulations: Ubiquitous Siamese Twins, Documenta Mathematics, ISMP, 2012, 419-431.
  • [9] G. Zwettler and W. Backfrieder, Functional Segmentation in 3D Angiography, Proc. of the 4th Forschungsforum der österreichischen Fachhochschulen FFH2010, Burgenland, Austria, 2010, 79-84.
  • [10] S. Hougardy, The Floyd-Warshall algorithm on graphs with negative cycles, Information Processing Letters 110, 2010, 279-281.
  • [11] K. Brodmann and L.J. Garey, Brodmanns: Localisation in the Cerebral Cortex, Springer, 2006.
  • [12] T. Kaltofen, G. Santana Sosa and S. Priglinger, Computer-Based Simulation of the Prism Cover Test with the Biomechanical Eye Model SEE-KID, Medicine Meets Virtual Reality 21, Manhattan Beach, USA, 2014.
  • [13] T. Kaltofen, G. Santana Sosa and S. Priglinger, SEE-KID - Virtual Ophthalmotrope Versus Biomechanical Model, 23rd Oculomotor Meeting, Linz, Austria, 2013.
  • [14] G. Zwettler, General Model-Based Segmentation Strategy for Holistic Analysis of Tomographic Medical Image Data in 3D Radiology, PhD Thesis, University of Vienna, Austria, 2014.
  • [15] R.E. Pattis, EBNF: A Notation to Describe Syntax, available from http://www.ics.uci.edu/pattis/ICS-31/lectures/ebnf.pdf (visited on 07/31/2014), 2013.
  • [16] Kitware Inc, VTK - The Visualization Toolkit, available from http://www.vtk (visited on 10/11/2013), 2013.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-070d5a9a-9453-4241-a147-6ffa8373e9f0
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