2006/10/25 1 A Virtual Endoscopy System Author : Author : Anna Vilanova 、 Andreas K ö nig 、 Eduard Gr ö ller Source :Machine Graphics and Vision, 8(3),

Slides:



Advertisements
Similar presentations
In the name of God ….
Advertisements

Games, Movies and Virtual Worlds – An Introduction to Computer Graphics Ayellet Tal Department of Electrical Engineering Technion.
GRAPP, Lisbon, February 2009 University of Ioannina Skeleton-based Rigid Skinning for Character Animation Andreas Vasilakis and Ioannis Fudos Department.
Real-Time Dynamic Wrinkles Caroline Larboulette Marie-Paule Cani GRAVIR Lab, Grenoble, France.
Character Animation from 2D Pictures and 3D Motion Data ACM Transactions on Graphics 2007.
Parameter Controlled Volume Thinning Nikhil Gagvani Deborah Silver.
NUS CS5247 Motion Planning for Camera Movements in Virtual Environments By Dennis Nieuwenhuisen and Mark H. Overmars In Proc. IEEE Int. Conf. on Robotics.
Vision Based Control Motion Matt Baker Kevin VanDyke.
3D M otion D etermination U sing µ IMU A nd V isual T racking 14 May 2010 Centre for Micro and Nano Systems The Chinese University of Hong Kong Supervised.
Eurohaptics 2002 © Interactive Haptic Display of Deformable Surfaces Based on the Medial Axis Transform Jason J. Corso, Jatin Chhugani,
Chapter 5 Raster –based algorithms in CAC. 5.1 area filling algorithm 5.2 distance transformation graph and skeleton graph generation algorithm 5.3 convolution.
D contour based local manual correction of liver segmentations1Institute for Medical Image Computing 3D contour based local manual correction.
Semi-Automatic Topology Independent Contour-Based 2 1/2 D Segmentation Using Live-Wire Semi-Automatic Topology Independent Contour-Based 2 1/2 D Segmentation.
HCI 530 : Seminar (HCI) Damian Schofield.
Exchanging Faces in Images SIGGRAPH ’04 Blanz V., Scherbaum K., Vetter T., Seidel HP. Speaker: Alvin Date: 21 July 2004.
Modeling and Deformation of Arms and Legs Based on Ellipsoidal Sweeping Speaker: Alvin Date:2/16/2004From:PG03.
Motion Planning for Camera Movements in Virtual Environments Authors: D. Nieuwenhuisen, M. Overmars Presenter: David Camarillo.
1 Image-Based Visual Hulls Paper by Wojciech Matusik, Chris Buehler, Ramesh Raskar, Steven J. Gortler and Leonard McMillan [
2007Theo Schouten1 Introduction. 2007Theo Schouten2 Human Eye Cones, Rods Reaction time: 0.1 sec (enough for transferring 100 nerve.
Interactive Manipulation of Rigid Body Simulations Presenter : Chia-yuan Hsiung Proceedings of SIGGRAPH 2000 Jovan Popovi´c, Steven M. Seitz, Michael.
Lecture 5: Interaction and Navigation Dr. Xiangyu WANG Acknowledge the notes from Dr. Doug Bowman.
Shading Languages By Markus Kummerer. Markus Kummerer 2 / 19 State of the Art Shading.
3-D Modeling Concepts V part 2.
I NTERACTIVE V OLUME R ENDERING FOR V IRTUAL C OLONOSCOPY IEEE Proceedings of Visualization, Phoenix, U.S.A., Oct. 1997, pp. 433 – 436 Presented.
Modeling and representation 1 – comparative review and polygon mesh models 2.1 Introduction 2.2 Polygonal representation of three-dimensional objects 2.3.
VIRTUAL PROTOTYPING of ROBOTS DYNAMICS E. Tarabanov.
IMPLEMENTATION ISSUES REGARDING A 3D ROBOT – BASED LASER SCANNING SYSTEM Theodor Borangiu, Anamaria Dogar, Alexandru Dumitrache University Politehnica.
Statistical analysis of pore space geometry Stefano Favretto Supervisor : Prof. Martin Blunt Petroleum Engineering and Rock Mechanics Research Group Department.
Multigenerational Analysis And Visualization of Large 3D Vascular Images Shu-Yen Wan Department of Information Management, Chang Gung University, Taiwan,
Constraints-based Motion Planning for an Automatic, Flexible Laser Scanning Robotized Platform Th. Borangiu, A. Dogar, A. Dumitrache University Politehnica.
Technology and Historical Overview. Introduction to 3d Computer Graphics  3D computer graphics is the science, study, and method of projecting a mathematical.
Introduction Tracking the corners Camera model and collision detection Keyframes Path Correction Controlling the entire path of a virtual camera In computer.
2008/10/02H704 - DYU1 Active Contours and their Utilization at Image Segmentation Author : Marián Bakoš Source : 5th Slovakian-Hungarian Joint Symposium.
© Manfred Huber Autonomous Robots Robot Path Planning.
Invitation to Computer Science 5th Edition
Automated generation of control skeletons for use in animation Author : Lawson Wade, Richard E. Parent Source : The Visual Computer (2002) 18: Speaker.
Exploitation of 3D Video Technologies Takashi Matsuyama Graduate School of Informatics, Kyoto University 12 th International Conference on Informatics.
CSCE 5013 Computer Vision Fall 2011 Prof. John Gauch
1 Interactive Thickness Visualization of Articular Cartilage Author :Matej Mlejnek, Anna Vilanova,Meister Eduard GröllerMatej MlejnekAnna VilanovaMeister.
Vision-based human motion analysis: An overview Computer Vision and Image Understanding(2007)
Semantic Wordfication of Document Collections Presenter: Yingyu Wu.
Chapter 7: Trajectory Generation Faculty of Engineering - Mechanical Engineering Department ROBOTICS Outline: 1.
Blood Vessel Modeling using 2D/3D Level Set Method
Daniele D’Agostino CNR - IMATI - Sezione di Genova
Scene Reconstruction Seminar presented by Anton Jigalin Advanced Topics in Computer Vision ( )
112/5/ :54 Graphics II Image Based Rendering Session 11.
Authors: I. Viola, A. Kanitsar, M. Gr ö ler Institute of Computer Graphics and Algorithms Vienna University of Technology, Austria Importance Driven Volume.
Approach Outline Polygonal-Functional Hybrids for Computer Animation and Games The modern world of computer graphics is mostly dominated by polygonal models.
A D V A N C E D C O M P U T E R G R A P H I C S CMSC 635 January 15, 2013 Quadric Error Metrics 1/20 Geometric Morphometrics Feb 27, 2013 Geometric Morphologyd.
City College of New York 1 John (Jizhong) Xiao Department of Electrical Engineering City College of New York Mobile Robot Control G3300:
3-D Information cs5764: Information Visualization Chris North.
Animation From Observation: Motion Editing Dan Kong CMPS 260 Final Project.
Planning Tracking Motions for an Intelligent Virtual Camera Tsai-Yen Li & Tzong-Hann Yu Presented by Chris Varma May 22, 2002.
Advisor : Ku-Yaw Chang Speaker : Ren-Li Shen /6/12.
Author :J. Carballido-Gamio J.S. Bauer Keh-YangLeeJ. Carballido-GamioJ.S. BauerKeh-YangLee S. Krause S. MajumdarS. KrauseS. Majumdar Source : 27th Annual.
1 Per-Pixel Opacity Modulation for Feature Enhancement in Volume Rendering Speaker: 吳昱慧 Date:2010/11/16 IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER.
3D Object Representations 2009, Fall. Introduction What is CG?  Imaging : Representing 2D images  Modeling : Representing 3D objects  Rendering : Constructing.
Visualization of Three-Dimensional Geometric Models in a Stereoscopic System Rositsa Radoeva Assistant professor at St. Cyril and St. Methodius University.
Shape2Pose: Human Centric Shape Analysis CMPT888 Vladimir G. Kim Siddhartha Chaudhuri Leonidas Guibas Thomas Funkhouser Stanford University Princeton University.
CIRP Annals - Manufacturing Technology 60 (2011) 1–4 Augmented assembly technologies based on 3D bare-hand interaction S.K. Ong (2)*, Z.B. Wang Mechanical.
1 Real-Time High-Quality View-dependent Texture Mapping using Per-Pixel Visibility Damien Porquet Jean-Michel Dischler Djamchid Ghazanfarpour MSI Laboratory,
Physically-Based Motion Synthesis in Computer Graphics
CSE 554 Lecture 2: Shape Analysis (Part I)
You can check broken videos in this slide here :
Real-time Wall Outline Extraction for Redirected Walking
3D Graphics Rendering PPT By Ricardo Veguilla.
Video-based human motion recognition using 3D mocap data
Computer Animation and Visualisation Lecture 4. Skinning
Chapter I Introduction
WELCOME.
Presentation transcript:

2006/10/25 1 A Virtual Endoscopy System Author : Author : Anna Vilanova 、 Andreas K ö nig 、 Eduard Gr ö ller Source :Machine Graphics and Vision, 8(3), pp , 1999 Speaker : Cheng-Jung Wu Advisor : Ku-Yaw Chang

2006/10/25 2 outline Introduction Introduction Structure of a Structure of a Virtual Endoscopy system Optimal path calculation Optimal path calculation Conclusion Conclusion

2006/10/25 3 Introduction Virtual endoscopy Virtual endoscopy a promising new technique a promising new technique explore hollow organs and anatomical cavities explore hollow organs and anatomical cavities Application Application non-invasive diagnostic endoscopy non-invasive diagnostic endoscopy educational purposes educational purposes special parts of the human body special parts of the human body a special field of application a special field of application

2006/10/25 4 VirEn Prototype Application snapshot Enlargement of the overview

2006/10/25 5 outline Introduction Introduction Structure of a Structure of a Virtual Endoscopy system Optimal path calculation Optimal path calculation Conclusion Conclusion

2006/10/25 6 Structure of a Structure of a Virtual Endoscopy system VirEn Interactive virtual endoscopy system

2006/10/25 7 Structure of a Structure of a Virtual Endoscopy system Two main issues accuracy diagnosis and surgical planning acquisition, segmentation and rendering user interaction clinical acceptance the navigation and the rendering

2006/10/25 8 Segmentation automatization accuracy : inversely proportional manual tedious and time-consuming semiautomatic accuracy due to user supervision being not as time consuming as a manual segmentation

2006/10/25 9 Rendering direct volume rendering directly visualize the volume data no segmentation required computationally expensive no loss of information surface rendering object of interest segmentation required a mesh of polygons not just the shape the surrounding tissue is important

2006/10/25 10 Navigation peculiarities inspect the internal part of an organ keeping the camera as close to the center of the hollow organ as possible

2006/10/25 11 Navigation module

2006/10/25 12 Optimal path generation skeleton the locus of points that are geometrically centered with respect to the object boundary

2006/10/25 13 Optimal path generation two techniques to extract a skeleton in discrete space Topological Thinning a mathematical foundation the connectivity preservation The Distance Transform Method the center of an object coincides with points having maximal distance to the borders less time consuming than the thinning operation

2006/10/25 14 Optimal path generation 1 2 3

2006/10/25 15 Camera motion Planned navigation computer animation and robot automatically calculate Smooth camera movements starting point to a target point the lack of interactivity Manual navigation control over all parameters without any constraints lost-in-space

2006/10/25 16 Camera motion Guided navigation control over the camera parameters some constraints motion too constrained : planned navigation no constraints : manual navigation camera metaphors viewpoint manipulation techniques a real world analogy flying, walking

2006/10/25 17 Camera motion

2006/10/25 18 outline Introduction Introduction Structure of a Structure of a Virtual Endoscopy system Optimal path calculation Optimal path calculation Conclusion Conclusion

2006/10/25 19 Optimal path calculation the prerequisites for intuitive navigation the prerequisites for intuitive navigation kept in the center of the hollow structure and connectivity is preserved kept in the center of the hollow structure and connectivity is preserved The thinning approach in VirEn the fully parallel 3D thinning algorithm

2006/10/25 20 Thinning algorithm a : fully parallel algorithm result b : not fully parallel algorithm result b artificial data a

2006/10/25 21 Thinning algorithm c : plus avoiding orientation dependencies b c

2006/10/25 22 Some results using a real data set Skeleton obtained by the topological thinning together with a transparent surface of the binary segmented data.

2006/10/25 23 outline Introduction Introduction Structure of a Structure of a Virtual Endoscopy system Optimal path calculation Optimal path calculation Conclusion Conclusion

2006/10/25 24 Conclusion A basic prototype based on VirEn Special effort navigation optimal path calculation Research and implementation effort direct volume rendering navigation structures Additional work camera motion model

2006/10/25 25 The End Thanks!