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Thoughts on Medical Visualization: Application Spots, Priorities, and SimVis

This article discusses various application spots for medical visualization, including screening, diagnosis, training/planning, and education/presentation. It also highlights relevant issues such as the integration of segmentation and registration, time-dependent and multi-dimensional data, and the use of InfoVis. The author presents their priorities for medical visualization, including interactive visual analysis, meeting the user's needs, and focusing on what to show rather than how to visualize. Lastly, the concept of SimVis is introduced, emphasizing the visualization of attribute space linked to spatial and temporal data.

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Thoughts on Medical Visualization: Application Spots, Priorities, and SimVis

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  1. Thoughts on Medical Visualization –my 2 [Euro-]cents Helwig Hauser VRVis Research Centerhttp://www.VRVis.at/

  2. Application Spots (1/2) • Screening • may take (almost) no time  as automatic as possible! • no searching if possible  one picture says it all?! • Example: virtual colonoscopy [Frits Post, Dagstuhl 2003] • faster • better • reliable • cleansing! • app. eng.! • evaluation! Thoughts on Medical Visualization

  3. Application Spots (1/2) • Screening […] • Diagnosis • may take a few minutes  no playing ‘round! • needs to be task-specific • requires robust, trusted techniques (no magic!) • Example: mammography [Bernhard Preim, Wien 2004] • contrast-enhancedMRI • time2peak,intensity • redundantvis. Thoughts on Medical Visualization

  4. Application Spots (2/2) • Training/planning • field of vis. opportunities! • success stories (virtual endoscopy, facial reconstr., …)! • more/better simulation needed (tissues) • addresses interface technology (haptics!) • Example: virtual pituitary surgery [André Neubauer, Austin 2004] • different modes • tissue simulation • haptic feedback • slices context Thoughts on Medical Visualization

  5. Application Spots (2/2) • Training/planning […] • Education/presentation • medical illustration • medical publications • time! • Example: NPR for medical illustration [Bernhard Preim, Bremen 2005] • focus+context • mix of styles • color vs. gray • accentuation • cut-away • annotations Thoughts on Medical Visualization

  6. Selected MedVis Issues • Make use of “cheap” data, e.g., x-ray images (just a few), ultra-sound data (4D!) • Better integration with segmentation, registr., etc.(visualizing segmented data, vision research) • MedVis  time-dependent(4D data, e.g., blood flow; patient history) • MedVis  multi-dimensional(multi-modal, multi-sensor) • InfoVis for MedVis(heterogeneous data) Thoughts on Medical Visualization

  7. [adapted from Bernhard Preim‘s 7 Golden Rules for MedVis, Dagstuhl 2003] Golden Rules • Be friend with 2D (link 2D & 3D, both: interaction) • Model-based visualization, application-specific • Avoid parameters (useful defaults) • Utilize segmentation if available • Emphasize (focus), semantically • Provide anatomical context • Visualize uncertainty • Allow for quantification • On-image interaction (avoid context switches) Thoughts on Medical Visualization

  8. My priorities (fast fwd recap) • Interactive visual analysis (cf. NVAC, etc.) • establishing a visual dialog user—data/information • allowing for asking questions about the data • Meeting the user (doctor) • knowing the user (and his/her tasks/challenges) • moving vis. interface language towards the users • Focus on what to show (as compared to how to vis.) • build-up of semantical layers on top of the data • focus+context visualization • Integration with other approaches (statistics, DM) • New stages of complexity (nD, time-dep., …) Thoughts on Medical Visualization

  9. SimVis • nD, time-dependent simulation data • visualization of attribute space (InfoVis) linked to visualization of spatial & temporal data • interact. user queries, example: show hot fluid which is slowand near the boundary(cooling jacket) • DPF example • SimVis.at Thoughts on Medical Visualization

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