1. DICOM INTERNATIONAL CONFERENCE & SEMINAR Oct 9-11, 2010 Rio de Janeiro, Brazil Managing Display Quality & Consistency Lawrence Tarbox, Ph.D. Washington University in St. Louis

2. Overview Review of Grayscale Standard Display Function Review of Grayscale Presentation State Color Presentation States –Color Consistency –Presentation States applied to Color Images –Color Blending - CT-PET fusion Hanging Protocols

3. Problems of Inconsistency mass visiblemass invisible VOI chosen on one display device Rendered on another with different display Mass expected to be seen is no longer seen Slide Provided by David Clunie, Quintiles Intelligent Imaging

4. Problems of Inconsistency 0.5 1.5 1.0 3.0 Not all display levels are perceivable on all devices Slide Provided by David Clunie, Quintiles Intelligent Imaging

5. Problems of Inconsistency Digital Modality Laser Printer Printed images does not look like displayed images Slide Provided by David Clunie, Quintiles Intelligent Imaging

6. Grayscale Standard Display Function Defines a standardize output ‘unit’ for monochromatic DICOM images called ‘P-Values’ (Presentation Values) Based on a model of human vision described by Barton, et al A mathematical derivation that takes into account lighting conditions Follows a curve that is roughly perceptually linear

7. Grayscale Standard Display Function.01.1 1 10 100 1000 02004006008001000 Grayscale Standard Display Function JND Index Same number of Just Noticeable Difference == Same perceived contrast Despite different change in absolute luminance Slide Provided by David Clunie, Quintiles Intelligent Imaging

8. Calibrate the Monitor! First set up monitor/graphics subsystem as optimally as possible Measure the ambient light Measure the current response of the monitor Calculate a calibration LUT that converts P- values into digital driving levels for the monitor Most high end medical imaging monitors can auto-calibrate

9. Display Calibration Tools (Photometer) Slide Provided by Jerry Gaskill, Image Smiths Inc.

10. Monitor Characteristic Curve 0.01 0.1 10 100 050100150200250300 Digital Driving Level Slide Provided by David Clunie, Quintiles Intelligent Imaging Luminance Ambient Light

11. Perceptual linear device - LUT Mapping P-Values to Input of Characteristic Curve (DDL’s) 0 50 100 150 200 250 300 050100150200250300 P-Values DDL Slide Provided by David Clunie, Quintiles Intelligent Imaging

12. Grayscale Standard Display Function.01.1 1 10 100 1000 02004006008001000 Grayscale Standard Display Function JND Index Same number of Just Noticeable Difference == Same perceived contrast Despite different change in absolute luminance Slide Provided by David Clunie, Quintiles Intelligent Imaging

13. Distributed Image Consistency Digital Modality Workstation Laser Printer Workstation Identical perceived contrast

14. DICOM Grayscale Presentation State Separate object from the image objects Specifies how the referenced image is to be displayed –Grayscale transformation –Graphics and text overlays –Spatial transformations

15. Transformation VOI LUT (Subtraction) Mask Modality LUT Transformation Annotation Image Transformation ShutterSpatial Transformation Annotation Disp. Area Presentation LUT Presentation LUT Transformation Window/Level or VOI LUT Rescale Slope/Intercept or Modality LUT Original Image Display P-Values Grayscale Transformations Shutter, Annotation and Spatial Transformations DICOM Grayscale Image Transformation Model

16. Spatial Transformations Original Image Entire Image Selected Transformed Image Scale To Fit Flip Horizontal

17. Spatial Transformations Original Image Part of Image Selected Transformed Image Scale To Fit Flip Horizontal

18. Transformation & Annotation Original Image Part of Image Selected Transformed Image Scale To Fit Flip Horizontal Mass behind heart In this example, - text annotation is specified by image relative visible anchor point - the circle is a separate image relative graphic annotation In this example, - text annotation is specified by image relative visible anchor point - the circle is a separate image relative graphic annotation

19. Limitations of Grayscale Presentation States Apply to grayscale images –no means to specify spatial transformations or graphic annotations for color images Only grayscale consistency –standard display function defined only for luminance No pseudo-color capability No blending or fusion capability

20. Distributed Color Image Consistency Digital Modality Workstation Printer Workstation Different perceived color

21. Distributed Image Consistency Digital Modality Workstation Printer Workstation Identical perceived color

22. True and Pseudo-Color

23. Goals for Color Color consistency –standard function –defined for image output space of existing color images Transformation and annotation pipeline Pseudo-color for grayscale images Blending of grayscale images –alpha blending function –colorizing superimposed image

24. Standard Color Space GSDF filled a void Color consistency already standardized ICC - International Color Consortium Graphics and pre-press industry CIE Colorimetry Profiles of input and output devices Commercial Off-The-Shelf color management software handles conversion Perceptual rendering intent

25. Three New SOP Classes Color Presentation State Pseudo-Color Presentation State Blending Presentation State ICC Profile –Defines output of all color presentation states –Optionally present in all color images PCS-Values (analogous to grayscale P- Values) –Profile Connection Space (CIELAB or CIEXYZ)

26. Commonality All presentation states share identical –Spatial transformation pipeline –Graphic and text annotation pipeline Choice of output space –P-Values for grayscale –PCS-Values for color and pseudo-color and blending

27. Old Grayscale Pipeline

28. Grayscale & Color Pipeline

29. Common Spatial & Annotation Pipeline

30. Blending Pipeline

31. Blending for CT-PET select superimposed select underlying

32. Blending for CT-PET select superimposed [register] select underlying

33. Blending for CT-PET select superimposed [register] resample select underlying

34. Blending for CT-PET select superimposed [register] resample within slices select underlying

35. Blending for CT-PET select superimposed [register] resample within slices [between slices] select underlying

36. Blending for CT-PET select superimposed [register] resample within slices [between slices] select underlying rescale and window

37. Blending for CT-PET select superimposed [register] resample within slices [between slices] select underlying rescale and window pseudo-color

38. Blending for CT-PET select superimposed [register] resample within slices [between slices] select underlying rescale and window blend pseudo-color

39. Color - Conclusion Color consistency using industry standard Transformation/annotation for color images Exchange of pseudo-color information Support for specifying sets of images to be blended, and how to blend (but not register or resample) them

40. Hanging Protocols “Default display protocols” A set of instructions How to layout a class of images for display Order, orientation, windowing, processing Not specific to a particular patient’s images Hence a protocol, not a presentation state

41. Hanging Protocols

42. New Study Old Lateral New Lateral New Frontal New Townes L L LL F F FF Old Study

43. Hanging Protocol Goals Encode –Applicability of protocol (type of display & images) –Selection of images –Display of selected images Store centrally, retrieve and exchange –Persistent composite objects –Query, retrieval and media encoding Vendor neutrality –Interchange between sites, PACS and workstations –Survive upgrades and replacements –“Public” library of “good” hanging protocols ?

44. Using a Hanging Protocol Given a current exam (e.g. reading worklist) Find potentially applicable protocols Retrieve them from archive Select one from those available Select image +/- other studies to which it applies Display selected images as instructed

45. Finding a Protocol Definition Module –Name, description, level, creator, creation datetime –Modality, anatomy, laterality –Procedure, reason for procedure –Number of priors Environment Module –Number of screens –Size(s) of screens –Color or grayscale bit depth

46. Selecting Images Definition of “image sets” By attribute values –Specific attributes, e.g. Modality, Anatomy –Specific values, e.g, CT, Chest –Supports all VRs, coded sequences, private elements and multi-frame functional groups By time –Relative time (today, yesterday, within last week) –Abstract priors (last, oldest, pre-operative, etc.)

47. Successful Selection All hanging protocols depend on consistent and reliable (and standard) information being present in the images DICOM Hanging Protocols don’t solve this integration problem Ideally - modality inserts correct anatomy and procedure and reason and orientation codes, and uses standard technique descriptions Worst case (typically?) - modality protocol (or operator) inserts recognizable Series Description

48. Information for Hanging Modality: Mammography Anatomic Region: Breast Image Laterality: L View Code: Medio-Lateral Oblique Patient Orientation: A\FR Anterior Foot Right L

49. Priors Concept of the “current” study required Protocol chooses priors based on –Relative time –Abstract temporal ranges (previous, last, etc.) –Abstract coded descriptions (“pre-operative”) Does NOT specify how to find them or get them May have been pushed, may need a query May be hard to find by abstract descriptions Creative use of queries or out-of-band information

50. Mapping to Image Boxes Image Sets are mapped to Image Boxes Image Box types –Tiled (e.g. 3x4) –Stack (single image paged manually) –Cine (time-based play back) –Processed (e.g. MPR, 3D) –Single (e.g. a place for a report or waveform) Specify –Scrolling mode –Playback rate

51. Mapping to Image Boxes Filtering –By attribute, or abstract, e.g. “category” of “image plane” “axial” Sorting –By attribute, or abstract, e.g. “along axis” “increasing” Orientation –E.g. rotate/flip until row left column posterior (L\P) Annotation –Patient demographics, technique and graphics on or off

52. Processing & Presentation Reformatting, e.g., MPR, 3D, slab Thickness, interval View direction, e.g., axial, sagittal, coronal Type, e.g., MIP, surface, volume VOI Type (windowing), e.g., brain, bone Pseudo-color type, e.g., hot iron Invert grayscale True size Synchronized scrolling (by Display Set number) Navigation and localization

53. Display of Image Boxes Entire display environment from 0,0 to 1,1 Individual screens are not distinguished

54. Display of Image Boxes Image Sets displayed in Image Boxes Image Boxes rendered at relative location

55. Hanging Protocols - Conclusion Interchangeable Vendor neutral Multi-modality Support selection of priors Full richness of current display modes Flexible Extensible Non-trivial to implement and retrofit Dependent on reliable image attributes