1 / 18

High-Level User Interfaces for Transfer Function Design with Semantics

High-Level User Interfaces for Transfer Function Design with Semantics. Christof Rezk Salama (Univ. Siegen , Germany) Maik Keller (Univ. Siegen, Germany) Peter Kohlmann (TU Vienna, Austria). Volume Visualization. Volume visualization techniques are mature from the technical point of view.

gitano
Download Presentation

High-Level User Interfaces for Transfer Function Design with Semantics

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. High-Level User Interfacesfor Transfer Function Design with Semantics Christof Rezk Salama (Univ. Siegen , Germany) Maik Keller (Univ. Siegen, Germany) Peter Kohlmann (TU Vienna, Austria)

  2. Volume Visualization • Volume visualization techniques are mature from the technical point of view. • Real-time volume graphics on commodity PC hardware • Multidimensional transfer functions/classification • Gradient estimation and local illumination on-the-fly • Memory management and compression for large volumes • Even global illumination techniques. • Is the ”volume rendering problem“ solved? • If you ask the computer scientist, he‘ll probably say „yes“. • If you ask the users, they will most likely say „no“

  3. Questions • Why are volume rendering applications so hard to use for non-experts? • Are volume rendering applications easy to use for us, the „experts“ ? • What features must appropriate user interfaces provide?

  4. The Mental Model Example taken from: Donald A. Norman The Psychology of Everyday Things

  5. Volume Visualization • Transfer Function Design: Mapping of scalar data to optical properties (emission/absorption) • Color table:Example: 1D TF for 12 bit Data, 4096 values x RGBA = 16384 DOF • Editors based on geometric primitives 2D Transfer Functions 1D Transfer Functions

  6. User Intention Examples: • „Fade out the soft tissue“ • „Sharpen the blood vessels“ • „Enhance the contrast“ Question: What actions are necessary? • Even the expert, who programmed the user interface, doesnot know this! • Mental model is inappropriate or missing! • Semantics are missing (leads to “gulf of execution”) • Result in trial-and-error

  7. User Semantic Level Visibility Sharpness Contrast High-Level Parameters (Primitive Shapes) Low-Level Parameters (Color Table) Application Abstraction Levels All previous approaches aim at reducing the complexity, the degrees of freedom. None of the prevous approaches tries to provide an appropriate mental model!

  8. Semantic Models • Restrict ourselves to one specific application scenario.Example: CT angiography from neuroradiology • The visualization task will be performed manually for multiple data sets.Visualization expertandmedical doctor! • Evaluate statistical information about the results: • Which parameter modifications are necessary to „make the blood vessels sharper?“ • Use dimensionality reduction (PCA) to create a semantic model

  9. Bone Brain/Soft Tissue Skin/Cavities Blood vessels Developing a Semantic Model Step 1: Create a template for the TF

  10. Developing a Semantic Model Step 2: Adapt the template to reference data

  11. Developing a Semantic Model Step 2: Adapt the template to reference data

  12. Principal Component Analysis Semantics Developing a Semantic Model Step 3: Dimensionality reduction Step 2: Adapt the template to reference data Reference Transfer Functions Semantic Model

  13. High-Level Control Semantic Model High-Level User Interface Transfer Function Semantic Model

  14. Semantic Model

  15. Prototype Implementation Applicable to „anything that can be described by a parameter vector“ • Take care of the scale! • PCA for entire parameter vector is not appropriate • Small details might be missed • Our solution: • Split transfer function into entities (=structures, groups of primitives with same scale) • Perform PCA separately for each entity • Reassemble the transfer function from the different entities

  16. Results CTA: intracranial aneurysms: • 512 x 512 x {120-160} @12bit, 100ml non-ionic contrast dye • 20 data sets for training / 5 data sets for evaluation MR brain surgery: • 256 x 256 x {150-200} @12bit (noisy, lower dynamic range ~10bit) • 10 data sets Evaluation of the model: Analytically: Stability of the eigenvectors (dot product > 0.9) • Stable for >12 data sets (regardless of individual choice) User Study: Labels removed from the user interface • Most semantics were correctly identified by non-expert users

  17. Conclusion • User Interface Design Strategies: • Reducing DOF is not enough. • Good user interfaces must provide an appropriate mental model • Not an attempt to create a single user interfaces for any visualization tasks • Create semantic models for examination tasks as specific as necessary • Building block for software assistants for medical diagnosis and therapy planning

  18. Acknowledgements • Bernd Tomandl MD, Neuroradiologie, Bremen • Christopher Nimsky MD, Neurochirurgie, Erlangen

More Related