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Ultrasound Visualization Pipeline A Survey

Ultrasound Visualization Pipeline A Survey. Å. Birkeland, V. Šoltészová, D. Hönigmann, O. H. Gilja, S. Brekke, T. Ropinski and I. Viola. 1. University of Bergen, Norway. 3. Haukeland University Hospital, Norway. 2 . n22 Research & Technology Transfer, Austria. 4.

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Ultrasound Visualization Pipeline A Survey

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  1. Ultrasound Visualization PipelineA Survey Å. Birkeland, V. Šoltészová, D. Hönigmann, O. H. Gilja, S. Brekke, T. Ropinski and I. Viola 1. University of Bergen, Norway 3. Haukeland University Hospital, Norway 2 . n22 Research & Technology Transfer, Austria 4. University of Münster, Germany

  2. Motivation for Ultrasound Visualization • Fetal examination • Cardiac • Gastro Åsmund Birkeland, University of Bergen

  3. Ultrasound Imaging Modality • Non-invasive • Cheap • High resolution • Spatially • Temporally • Noise • Random • Speckle Åsmund Birkeland, University of Bergen

  4. Ultrasound Image Modality • 2D ultrasound • 3D ultrasound • Dedicated 3D ultrasound probe • 3D freehand ultrasound • 4D ultrasound • Blood flow • Doppler • B-flow Åsmund Birkeland, University of Bergen

  5. Ultrasound Visualization – The Pipeline • Pre-processing: Processing ultrasound data prior to segmentation, registration or rendering. • Segmentation: Extracting features from ultrasound data. • Registration: Combining ultrasound data with other types of medical imaging modalities. • Rendering: Presenting ultrasound data. • AugmentedReality: Combining ultrasound rendering Åsmund Birkeland, University of Bergen

  6. Ultrasound Visualization - The Pipeline Åsmund Birkeland, University of Bergen

  7. Pre-processing • Reconstruction of freehand ultrasound Large volumes • Data Enhancement Filltering Gee et al. Processing and Visualizing Three-Dimensional Ultrasound Data Åsmund Birkeland, University of Bergen

  8. Segmentation Automated assessment of ovarian follicles using a novel three-dimensional ultrasound software MagiCut– Interactive clipping for 3D ultrasound Åsmund Birkeland, University of Bergen

  9. Registration • Combining two or more image modalities in the same reference frame • Rigid Registration • Non-Rigid Registration Olesch et al. Matching CT and Ultrasound data of the Liver by Landmark constrained Image Registration Åsmund Birkeland, University of Bergen

  10. Rendering • Surface Rendering • 3D freehand rendering • 4D ultrasound Fattal and LischinskiVariationalClassification for Visualization of 3D Ultrasound Data Åsmund Birkeland, University of Bergen

  11. Rendering – Transfer Functions • Mapping data to color and opacity • Non-uniform data intensities for the same tissue Hönigmann et al. Adaptive Design of a Global Opacity Transfer Function for Direct Volume Rendering of Ultrasound Data Åsmund Birkeland, University of Bergen

  12. Rendering – Multi-Modal • Doppler • MRI / CT • Increase in image clutter Viola et al. Illustrated Ultrasound for Multimodal Data Interpretation of Liver Examinations Petersch et al. Blood flow in its context: Combining 3D B-Mode and Color doppler Ultrasonic Data Åsmund Birkeland, University of Bergen

  13. Rendering - Shading Ropinski et al. Interactive Volumetric Lighting Simulating Scattering and Shadowing Šoltészová et al. Multi-Directional Occlusion shading Chromatic Depth Coloring Åsmund Birkeland, University of Bergen

  14. Ultrasound and Augmented Reality 14 Åsmund Birkeland, University of Bergen Åsmund Birkeland, University of Bergen

  15. Acknowledgements • Illustrasound Project, VERDIKT, The Norwegian Research Council • Helwig Hauser – VisGroup, University of Bergen, Norway Åsmund Birkeland, University of Bergen

  16. Questions? • Thank you! Åsmund Birkeland, University of Bergen

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