Performance for RadiologicalDisplay Devices

Michael Flynn

Dept. of Radiology

mikef@rad.hfh.edu

RADIOLOGY RESEARCH

Health System

Henry Ford

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iQC Test Pattern (pacsDisplay)

Projection Test Pattern

12 / 0

12 / 0243 / 255

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Intro: visual interpretation

The device used to display radiographic images must effectivelytransfer spatial and contrast information to the human observer.

DETECTION DISPLAY

(A) Subject contrast in the patient is;(B) recorded by the detector and(C) transformed to display values that are(D) and sent to a display device for presentation to(E) the human visual system and interpretation.

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Intro: Visual Requirements

The performance of the human visual system (HVS)is reviewed in relation to display for the primaryinterpretation of radiological images.

A. Viewing Distance

B. Display Size

C. Pixel Size

D. Display Zoom

E. Equivalent Contrast

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A. Viewing Distance?

•Vergence•Accomodation

• Vergence (convergence)allows both eyes to focusthe object at the sameplace on the retina.

• The closer the object,the more the extraocularmuscles converge theeyes inward towards thenose.

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A. Viewing distance and vergence

Resting Point of Vergence

The eyes have a resting point of vergence of about 40inches.(Jaschcinsk-Kruza 1991).

– Objects closer than the resting point cause muscle strain.

– The closer the distance, the greater the strain (Collins 1975).

Every one of the subjects studied by Jaschinski-Kruza(1998) judged the eye to screen distance of 20 inchesto be too close. All accepted a 40 inch distance.

Grandjean (1983) reported an average preferredviewing distance of 30 inches.

Arms length viewing distance

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A. Viewing distance and accomodation

Resting Point of Accommodation

The ciliary muscle changes the shapeof the lens to focus the object.

– The eyes have a resting point ofaccommodation which is thedistance that the eye focuses towhen there is nothing to look at(Owens 1984).

– This resting point averages about31 inches (Krueger 1984).

Prolonged viewing of a monitor closer than the restingpoint of accommodation increases eye strain (Jaschinski-Kruza 1988). The ciliary muscle must work 2.5 timesharder to focus on a monitor 12 inches away than it doesto focus at 30 inches.

Arms length viewing distance

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B. Display Size?Field of view in relationto viewing distance.

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Rod receptors have highsensitivity, gray response,and interconnections thatrespond to motion.

The retina contains a largenumber of rod receptors(160 M) distributed overthe peripheral field.

B. HVS: peripheral response

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B. Display Size vs Viewing Distance

Diagonal SizeViewing DistanceTask

110.1 inches3 metersTeaching Conference

31.5 inches1 meterConsultation viewing

20.8 inches2/3 meterNormal viewing

10.4 inches1/3 meterClose Inspection

For a specific viewing distance the diagonal dimensionshould be about 80% of the viewing distance. (44o)

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B. Field of View

21 inch (diagonal) monitors with a field of 32 x 42 cmprovide an effective field for radiographic imagesviewed at a normal distance (2/3 m).

Eyeglasslensshould beoptimizedfor anormalviewingdistance

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C. Pixel Size?

•Visual Acuity•Contrast Sensitivity

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C. Visual Acuity

A variety of test patterns are used to assess visualacuity. Clinical measures are done typically with aSnellen eye chart. Much psychovisual research hasbeen done using sinusoidally modulated test targets.

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C. HVS: Retinal anatomy

The retina of the human eye contains a network ofrods and cones interconnected by neural cells.

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Particularly thin cones (2 m)are densely packed in thecentral 50 microns of the foveacentralis. They provide highdetail color response.

At 60 cm, 1 degree correspondsto a 1 cm field of view. Thisarea is focused on a 288 micronregion of the retina, the fovea

C. HVS: Foveal response

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C. Contrast Sensitivity as a measure of spatial acuity

Contrast sensitivity is the inverse of contrast threshold: Cs = 1/Ct

~2.5 c/mm

10% max

~0.5 c/mm

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• The eye perceives luminance variations as a changewith respect to viewing angle.

• Data on visual performance must always be converted fromcycles/degree to cycles/mm at a specified viewing distance.

Cycles/mm = 57.3 x (cycles/degree) / (viewing distance, mm)

C. Spatial Frequency: cycles/degree

mm

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C. Pixel Size at Maximum Spatial Acuity

The visual spatial frequency limit and associated pixel size canbe defined as that for which Cs = 10% of maximum.

The pixel size of a display system that matches the resolvingpower of the human eye depends on the observation distance.

Distance frequency pixel size

Close inspection 5 cycles/mm 0.100 mm/pixel

(0.33 m)

Normal viewing 2.5 cycles/mm 0.200 mm/pixel

(0.66 m)

Consultation view 1.7 cycles/mm 0.300 mm/pixel

(1.00 m)

Conference room 0.5 cycles/mm 1.000 mm/pixel

(3.00 m)

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C. Pixel array and Megapixels

The pixel size and the field of view dictate the pixelarray size and the total number of pixels.

Megapixels alone is not a good descriptor of quality.

Field of View pixel size array size MegaPixels

21 inch 0.100 mm 3200 x 4200 13.4

21 inch 0.200 mm 1600 x 2100 3.4

• idtech 3 MP panel20.8 inch (32 x 42 cm) 3.1 megapixels (.207 mm pixels)

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C. LCD 2MP Colot Pixel

LCD Pixel Structure

For a pixel pitch greater than ~200 microns, the pixelstructure is visible as a granular pattern.

Some consumer monitors have a granular diffusingsurface that creates a random noise pattern.

Dual Domain pixel structure Single Domain pixel structure

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D. Display Zoom?

Detector Detail in relation toDisplay Acuity

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D. Viewing distance and image zoom

Use of image zoom features is ergonomically better thanleaning forward for close inspection.

Split deck tables with a broad front deck usefully prohibitclose inspection with 3 MP monitors.

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D. Magnification / Minification

Minification has value byincreasing the frequency ofdiffuse structures.

1X

1/4X4X

1X

Zoom is needed to display detail atthe detector pixel level with goodcontrast sensitivity.

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D. True Size

For some applications, “true size”display is important.

– Comparison of current andprior exams obtained ondifferent detectors (or withscreen-film).

– Orthopedic assessment ofsize.

This requires knowledge of

– Detector element (del) pitch

– Display element (pixel) pitch.

Prior

Current

* adapted from D. Clunie, SCAR 2005

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D. Re-sampling for Display

A subset of imagevalues is re-sampledfor presentation on adisplay device.

In General;

• The detector and displaypixel spacings are different.

• The detector and displayoverall size are different

DETECTOR

DISPLAY

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D. Up-sampling (magnification)

Up sampling occurswhen the number ofdisplay values in theregion re-sampled ismore than the numberof recorded imagevalues .

This is commonlyencountered whendisplaying CT and MRimages.

• Blue circles show an 11x11array of recorded imagepixel values.

• Green solid circles are for a15 x 15 array of displaypixel values

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D. down-sampling (minification)

Down sampling occurswhen the number ofdisplay values in theregion re-sampled isless than the numberof recorded imagevalues .

This is commonlyencountered when afull radiograph isdisplayed.

• Blue circles show an 11x11array of recorded imagepixel values.

• Green solid circles show a7 x 7 array of display values.

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D. Interpolation

Estimation of variably spaced displayvalues from a set of image values is doneusing mathematical interpolation methods.

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Bi-Linear Interpolation

• Image values pairs above & below thedisplay value are linearly interpolatedbased on the column position (black).

• These values are linearly interpolatedbased on the row position.

D. Approximate Interpolation

While fast, nearest neighbor and bi-linear interpolation do notresult in optimal image quality due to artifacts and blur.

Nearest Neighbor Interpolation

• Display value (green) is taken as theimage value (blue) at the nearest rowand column.

• Produces visible block artifacts forlarge magnification.

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D. Improved Interpolation

Improved quality can be achieved byestimating display values from theclosest 16 image values (4 x 4).

–– SplineSpline interpolationinterpolation uses polynomialarc segments constrained to besmooth (1st and 2nd derivatives) attransition points (nodes). It hasbeen classically used for digitalimages.

– A still popular technique known ascubic convolutioncubic convolution involves the use ofa sinc-like kernels composed ofpiecewise cubic polynomials.

– Recent work has shown thatgeneralizedgeneralized splinespline interpolationinterpolation usinga pre-filter operation providesexcellent performance with fastimplementation and can providecontrolled smoothing.

Cubic Interpolation

• Display value (green) is computedfrom the closest 16 image values.

• The weighting functions for the 16image values are intended to estimatea continuous function within the spacebetween the sampled values.

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D. Magnification / Minification

Magnification: Calcified duct, 4:1 re-sampling 5.25 x 5.25 mm region

Nearest Neighbor

A

Bi-Linear

B

Cubic

C

Minification.

• Advanced interpolation methods can also provide effectiveminification with noise reduction (low-pass filter).

• Alternatively, minification is often done using multi-scalerepresentations of the image with progressive presentation.

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D – Display Interpolation – key points

Interpolation and Image Quality:

The numerical approach used to obtained magnifieddisplay values has significant impact on image quality.

Modern interpolation with good performance needsoptimal implementation for high speed.

Minification and noise reduction:

Minification should be done such that high frequencynoise (quantum mottle) is reduced.

Multi-scale representation of image date provides ameans for minification (JPEG 2000, JPIP, Wavelet, ..).

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E. Equivalent Contrast?

• Grayscale response• Luminance ratio (L’max/L’min)

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E. Contrast detection in relation to brightness

• Contrast detection is diminished for images with low brightness.

• Extensive experimental models have documented the dependenceof contrast detection on luminance, spatial frequency, orientationand other factors. The empirical models of either S. Daly or J.Barton provide useful descriptions of this experimental data.

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E. Contrast threshold vs luminance

The Barton model describes the average contrastthreshold of normal observers. Significant differencesexist for individual observers for different test methods

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E. DICOM graylscale display standard

DICOM part 3.14 describes a grayscale response thatcompensates for visual deficits at low brightness

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E. Fixed versus variable adaptation

Contrast threshold for varied visual adaptation (A, Flynn 1999b) and fixed(B) visual adaptation: The contrast threshold, L/L, for a just noticeabledifference (JND) depends on whether the observer has fixed (B) or varied(A) adaptation to the light and dark regions of an overall scene.

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E – Ct for small sinusoidal patterns on a color LCD.

2AFCassessment ofCt using variedbackgroundregionbrightness.

SINE and ADAPT Contrast Thresholds Normalized to SINE

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0.1 1 10 100

L/L_SINE

Re

lati

ve

CT

/CB

M

DB

DP

MF

MP

PT

PR-80

SL

AVERAGE

Effects of adaptation on observers contrastthresholds relative to changes in background.

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E. Adapted Observer Performance

Observer performance is best when visual system isadapted to the average scene luminance.

A B C

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E. Effect of Lmax/Lmin

Digital radiographsshould be displayedusing over aluminance range of250-350:1.

Images preparedfor range of 250that are display ona monitor with largerange will havepoorly perceivedcontrast in darkregions.

250:1650:1

250:1 .1 to 2.50 OD350:1 .1 to 2.65 OD650:1 .1 to 2.90 OD

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E. LR for LCD monitors

For CRT monitors, LR is set by adjustingbrightness (Lmin) and contrast (Lmax).

For LCD devices, only the backlightintensity can be adjusted.

For LCD devices

– Lmax is set by adjusting the backlightbrightness (current control).

– Lmin is set as a part of the grayscale calibration(starting LUT value).

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Other issues

Issues that I have not addressed!

• LCD devices have significant contrast changeswhen viewed at angles oblique to the surface.

• Note: New OLED technologies promise toeliminate that problem in near future.

• Pixel noise is poorly documented for new LCDmonitors. Further works needs to be done tounderstand whether pixel noise effects diagnosticvisual performance.

• 256 (8bit) versus 1024 (10bit) gray levels.

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Questions?