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5 May 2004 Augmented-reality-based segmentation refinement
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Abstract
Planning of surgical liver tumor resections based on image data from X-ray computed tomography requires correct segmentation of the liver, liver vasculature and pathological structures. Automatic liver segmentation methods frequently fail in cases where the anatomy is degenerated by lesions or other present liver diseases. On the other hand performing a manual segmentation is a tedious and time consuming task. Therefore Augmented Reality based segmentation refinement tools are reported, that aid radiologists to efficiently correct incorrect segmentations in true 3D using head-mounted displays and tracked input devices. The developed methods facilitate segmentation refinement by interactively deforming a mesh data structure reconstructed from an initial segmentation. The variety of refinement methods are all accessible through the intuitive, direct 3D user interface of an Augmented Reality system.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexander Bornik, Bernhard Reitinger, Reinhard Beichel, Erich Sorantin, and Georg Werkgartner "Augmented-reality-based segmentation refinement", Proc. SPIE 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, (5 May 2004); https://doi.org/10.1117/12.535478
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