1 / 51

Medical Images Visualization at the Computer Graphics Group/UFRGS

Medical Images Visualization at the Computer Graphics Group/UFRGS. Carla Maria Dal Sasso Freitas February, 2000. Summary. 1. Introduction 3. CG Group overview Previous works 4. Current project: VPat 5. Final comments. 1. Introduction. 1. Introduction. Porto Alegre 470,25 km 2

amanda
Télécharger la présentation

Medical Images Visualization at the Computer Graphics Group/UFRGS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Medical Images Visualization at the Computer Graphics Group/UFRGS Carla Maria Dal Sasso Freitas February, 2000

  2. Summary 1. Introduction 3. CG Group overview • Previous works 4. Current project: VPat 5. Final comments

  3. 1. Introduction

  4. 1. Introduction • Porto Alegre • 470,25 km2 • Population: ~ 1,286.251 • Climate: Subtropical wet with four well-defined seasons • Higher education: 4 large universities (each one with more than 20K students) and several small colleges

  5. 1. Introduction • UFRGS (Federal University of Rio Grande do Sul) • Created in 1895 • One of the top five universities in Brazil, both in size and quality • ~ 2,278 faculty members • Students: ~ 25,286 (undergraduate and graduate)

  6. 1. Introduction • Informatics Institute • Teaching and research since 1968 • Established as an Institute in 1989 • Departments • Applied Computing • Theoretical Computing

  7. 1. Introduction • Faculty • 69 professors (INPG, Grenoble; Karslruhe and Stuttgart, Germany; Newcastle, UK; Stanford, USA; Coimbra, Portugal; Louvain, Belgium; Amsterdam, Netherlands; ...) • Students: 700 undergraduate level + 270 graduate level • Courses at graduate level • M.Sc. in Computer Science • Ph.D. in Computer Science • Professional education

  8. 1. Introduction • Research areas • Computer Graphics and Image processing • Computer Architecture/Parallel Processing • Microelectronics/Digital Systems • Data Base Systems • Fault Tolerance • Software Engineering • Theoretical Computer Science • Artificial Intelligence • Computational Mathematics • Computer Networks/Communication • Formal Methods

  9. 2. CG Group Overview • Started in 1978, with one professor only • People • 4 Professors • 1 Post-doc • 5 Ph.D. Students • 18 M.Sc. Students

  10. 2. CG Group Overview • Research in the 80's: CAD • Research in the 90's • Rendering and animation • Scientific visualization • Meteorological data • Geological data • Medical images • Image processing techniques

  11. 3. CG Group Overview • Previous works regarding medical images • Nedel at EPFL • Freitas and group at UFRGS

  12. 3. CG Group Overview • Previous works • Nedel at EPFL • Freitas and group at UFRGS

  13. 3. CG Group Overview • Previous works • Nedel at EPFL • Freitas and group at UFRGS

  14. 3. VPat (Visualization and interaction with Virtual Patients) • Goals • Generation of virtual human models (virtual patients) to use in medical applications such as simulation of surgery and training • Movement simulation • Development of a framework to guarantee software reuse • Integration of the existing tools

  15. 3. VPat • Activities • Design of the OO framework • Volume visualization • 3D reconstruction of the human parts from real data • Motion simulation and body deformation (anatomic simulation of human bodies)

  16. 3. VPat • Activities • Design of the OO framework • Volume visualization • RenderVox improvement and conversion to the VPat framework • Survey about collaborative visualization • Multimodal visualization • 3D reconstruction of the human parts from real data • Motion simulation and body deformation (anatomic simulation of human bodies

  17. 3. VPat • Multimodal visualization with RenderVox • MRI and PET data obtained from different patients, no registration algorithm used (Marcelo Silva, 2000)

  18. 3. VPat • Multimodal visualization: ongoing work • Data obtained from the same patient • Cooperation with the best hospital in Brazil • INCOR/University of Sao Paulo • Study of registration methods (Isabel Manssour’s PhD thesis)

  19. 3. VPat • Activities • Design of the OO framework • Volume visualization • 3D reconstruction of the human parts from real data • Marching cubes implementation • Study of multi-resolution techniques • Motion simulation and body deformation (anatomic simulation of human bodies)

  20. 3. VPat • Activities • Design of the OO framework • Volume visualization • 3D reconstruction of the human parts from real data • Motion simulation and body deformation (anatomic simulation of human bodies) • Mechanical modeling of joints • Skeleton motion control • Soft tissue deformation

  21. 3. VPat • Surgery simulation (Luciana Nedel, 1999)

  22. 3. VPat • Activities • Design of the OO framework • Volume visualization • 3D reconstruction of the human parts from real data • Motion simulation and body deformation (anatomic simulation of human bodies)

  23. 4. Final comments • Related works in our group • Interactive segmentation of medical images • Olabarriaga, 1999 with A. Smeulders, Amsterdam • Development of new filtering techniques • Scharcanski & Jung, 1999/2000 • ultrasound images from fetal hearts • mammographic images

  24. http://www.inf.ufrgs.br/cg

  25. Collaborative Visualization in Medicine (WSCG 2000, February 7-11, Plzen) • Goal: Medical data visualization overview • Different approaches for collaborative visualization • To get knowledge about difficulties for its utilization

  26. Collaborative Visualization in Medicine • CSCW (Computer Support for Cooperative Work) • New successful area • People in different places working together • CSCV (Computer Support for Collaborative Visualization) • Subset of CSCW applications • Shared visualization and control parameters • Challenge: multi-user interactive applications

  27. User A Data Filtering(F) Filtering(F) Mapping(M) Mapping(M) Render(R) Render(R) Data Image Image User B Shared Data Shared Control Collaborative Visualization in Medicine • Visualization pipeline (Haber & McNabb, 1990) extension to achieve collaboration

  28. Collaborative Visualization in Medicine • Telemedicine • Communication technology used to support interaction between physicians and patients • Applications • Remote clinical consultation • Telesurgery, teleradiology • Collaborative diagnosis • Collaborative visualization systems applied to Medicine • Image presentation to remote collaborators • Image-based interaction

  29. Collaborative Visualization in Medicine • TeleInViVo • Fraunhofer Center for Computer Graphics, DARPA e MATMO • Main goals • Therapy planning and treatment • Medical training, surgery and diagnosis

  30. Collaborative Visualization in Medicine • TeleMed • Los Alamos National Laboratory and National Jewish Center for Immunology and Respiratory Medicine • Prototype of the Virtual Patient Records (VPR) • Main goal • Standardize the electronic management of patient information

  31. Collaborative Visualization in Medicine • Current trend • Use of the Web as a collaboration environment • Challenges and open questions • Communication technology • Identification (security) handling • Shared data coherence • Synchronization of user activities • User-friendly interface • Real-time visualization and interaction • VR devices accuracy and touch-feedback • Realistic images

  32. Collaborative Visualization in Medicine • The building of a collaborative system is an interdisciplinary effort • User-centered approach • Efficient data management • Object-oriented design and programming • Collaborative systems have to be improved to become attractive work tools • Several difficulties for the real utilization of such systems are still found

  33. Nedel at EPFL(Ph.D. Thesis) • The skeleton • Anatomic modeling of skeletons • Joints position ( Luciana Nedel, 1998)

  34. Nedel at EPFL ( Luciana Nedel, 1998)

  35. Nedel at EPFL • Simulation of the muscles action • Action lines • Represent mechanically the force that a muscle produces on a bone • Composed by an origin, an insertion and optionally by one or more control points (Luciana Nedel, 1998)

  36. Nedel at EPFL • Muscles deformation • Mass-spring deformation model • Example: extension • Example: compression (Luciana Nedel, 1998)

  37. Nedel at EPFL • Example: reconstructed muscle (Luciana Nedel, 1998)

  38. Nedel at EPFL • Framework to allow the human body modeling and simulation • Body Builder Plus - integration tool • Allows the design of human models created entirely with bones and reconstructed muscles • Combines deformable muscles with metaballs representing some muscles, organs and fat tissues

  39. Nedel at EPFL • Body Builder Plus: examples... (Luciana Nedel, 1998)

  40. RenderVox • Interactive volume visualization of medical images using ray casting • Available tools • Navigation through the slices data set • Cutting planes • Cutting volume/ subvolume • Hybrid (geometric and volume) visualization • Multimodal visualization

  41. RenderVox • Camera control and slice visualization Marcelo Silva, 1999

  42. RenderVox • Interactive interface (Marcelo Silva, 1998/2000)

  43. RenderVox • MRI of a head (Marcelo Silva, 1998)

  44. RenderVox • Transparency levels using classification tables (Marcelo Silva, 1998)

  45. RenderVox • Cutting with planes (Marcelo Silva, 1998/1999)

  46. RenderVox • Cutting with volumes (Marcelo Silva, 1998/1999)

  47. RenderVox • Cutting with planes and volumes (Marcelo Silva, 1998/1999) • Cutting with non-planar tools (Marcelo Silva, 1998/1999)

  48. RenderVox • Hybrid rendering (geometric models & volume data) (Marcelo Silva, 2000)

  49. GeoVis • Visualization of layers 1 and 2 of characteristic “Marcos de Inundação”, grid dimension 30 x 30, layer 1 in wireframe (Karen Basso, 1999)

  50. GeoVis • Visualization of layer 1 of characteristic “Marcos de Inundação”, and “Isolita” attribute. (Karen Basso, 1999)

More Related