Managing Display Quality & Consistency

1. 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 • VOI chosen on one display device • Rendered on another with different display • Mass expected to be seen is no longer seen mass visible mass invisible Slide Provided by David Clunie, Quintiles Intelligent Imaging

4. 0.5 1.0 • Not all display levelsare perceivable on alldevices 1.5 3.0 Problems of Inconsistency Slide Provided by David Clunie, Quintiles Intelligent Imaging

5. Digital Modality Laser Printer Problems of Inconsistency Printed images does not looklike 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 Despite different change in absolute luminance 1000 100 10 1 0 200 400 600 800 1000 .1 .01 JND Index Same number of Just Noticeable Difference == Same perceived contrast Grayscale Standard Display Function 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 Monitor Characteristic Curve Luminance 100 10 0.1 Ambient Light 0.01 0 50 100 150 200 250 300 Digital Driving Level Slide Provided by David Clunie, Quintiles Intelligent Imaging

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

12. Grayscale Standard Display Function Despite different change in absolute luminance 1000 100 10 1 0 200 400 600 800 1000 .1 .01 JND Index Same number of Just Noticeable Difference == Same perceived contrast Grayscale Standard Display Function Slide Provided by David Clunie, Quintiles Intelligent Imaging

13. Laser Printer Digital Modality Workstation Workstation Distributed Image Consistency 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. DICOM Grayscale Image Transformation Model Rescale Slope/Intercept or Modality LUT Window/Level or VOI LUT Presentation LUT Original Image Presentation LUT Transformation M o d a l i t y M a s k V O I L U T L U T Grayscale Transformations ( S u b t r a c t i o n ) T r a n s f o r m a t i o n T r a n s f o r m a t i o n S h u t t e r Display P-Values T r a n s f o r m a t i o n I m a g e D i s p . A r e a S p a t i a l Shutter, Annotation and Spatial Transformations T r a n s f o r m a t i o n A n n o t a t i o n A n n o t a t i o n

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

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

18. Transformation & Annotation Part of Image Selected Flip Horizontal Scale To Fit Mass behind heart Mass behind heart Original Image Transformed Image 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. Printer Digital Modality Workstation Workstation Distributed Color Image Consistency Different perceived color

21. Printer Digital Modality Workstation Workstation Distributed Image Consistency 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 selectunderlying selectsuperimposed

32. Blending for CT-PET selectunderlying [register] selectsuperimposed

33. Blending for CT-PET selectunderlying [register] selectsuperimposed resample

34. Blending for CT-PET selectunderlying [register] within slices selectsuperimposed resample

35. Blending for CT-PET selectunderlying [register] within slices selectsuperimposed resample [between slices]

36. Blending for CT-PET selectunderlying rescale andwindow [register] within slices selectsuperimposed resample [between slices]

37. Blending for CT-PET selectunderlying rescale andwindow [register] within slices selectsuperimposed pseudo-color resample [between slices]

38. Blending for CT-PET selectunderlying rescale andwindow blend [register] within slices selectsuperimposed pseudo-color resample [between slices]

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. L L L L Old Lateral New Frontal New Townes New Lateral F F F F New Study Old Study Hanging Protocols

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

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