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Surface Modeling Visualization using BrainVISA Bill Rogers UTHSCSA – Research Imaging Center.

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Presentation on theme: "Surface Modeling Visualization using BrainVISA Bill Rogers UTHSCSA – Research Imaging Center."— Presentation transcript:

1 Surface Modeling Visualization using BrainVISA Bill Rogers UTHSCSA – Research Imaging Center

2 Why Use Surface Modeling Visualization of Structure Analysis of Structure Dynamic control of view

3 What Makes a Surface A surface is usually defined as a mesh The mesh is composed of vertices, edges, normals and polygons The vertices define the surface boundary Vertices are connected by edges Edges are combined to make polygons Normals determine side of surface as well as viewing properties

4 Vertices and Edges

5 Polygons

6 Polygon Mesh Surface

7 Parametric Surfaces Surface in Euclidean space defined by a parametric equation with two parameters A set of weighted control points determine the location of individual surface points The come in several flavors including Bezier, B-Spline, NURBS

8 NURBS surface with control points

9 NURBS Surfaces

10 Isosurface extraction or Where to put the surface

11 Isosurfaces A 3-D surface corresponding to points with a single scalar value (or narrow range of values). The scalar value corresponds to an interface between voxels of different properties.

12 The Surface is Only as Good as the Tissue Classification Bias Correction Partial Volume Effect Classification of voxels

13 Isosurface Extraction Techniques Geometric Decomposition Techniques –Geometric techniques retain the original representation of the volume and partition along divisions in the voxel volume Span Space Decomposition Techniques –Span space decomposition techniques create and manipulate abstract representations of the voxels

14 Methods of Isosurface Extraction Marching Cubes (Geometric) BONO - branch-on-need octree (Geometric) ISSUE - Isosurfacing in Span Space with Utmost Efficiency (Span Space) Interval Tree – (Span Space)

15 Marching Cubes William E. Lorensen, Harvey E. Cline: Marching Cubes: A high resolution 3D surface construction algorithm. In: Computer Graphics, Vol. 21, Nr. 4, July 1987 Computes polygons where the isosurface passes through eight nearest neighbors Gradient of scalar value at each grid point used for surface normal Other algorithms are always compared to Marching Cubes

16 Marching Cubes 15 Unique cube configurations that can be rotated and reflected to 256 configurations

17 Marching Cubes Demo Graphics cards aren’t just for games anymore

18 Mesh Segmentation

19 Introduction to BrainVisa Origin and Development Collaborative work of methodologists of the Institut Fédératif de Recherche Core development now at the Service Hospitalier Frédéric Joliot Framework for Image Processing GUI for chaining applications together –GUI developed in Python –Command line application developed in C++ Database for organization of input and output files Visualization package for viewing results

20 BrainVISA Availability Multiplatform –Linux (Fedora, Redhat, Mandriva) –Macintosh (OS X) –Windows (2000, XP) Download at http://brainvisa.info/http://brainvisa.info/

21 BrainVISA Demo

22 BrainVISA Curvature Mapping

23 BrainVISA Cortical Folds

24 RIC BrainVisa Extensions

25 RIC Cortical Thickness

26 White matter surface normals

27 RIC Sulcal Length and Depth

28 Mapping Mesh to Volume

29 RIC 3D Gyrification Index

30 Removing Effect of Ventricles


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