Viewing images on and off axis with CRT and LCD monitors: effects on observer and model performance

Krupiński, Elizabeth A.; Johnson, Jeffrey P.; Roehrig, Hans; Nafziger, John S.; Lubin, Jeffrey

doi:10.1117/12.592216

Cited by 2 publications

(2 citation statements)

References 16 publications

(27 reference statements)

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“…Additional information about the test conditions and observer performance results are provided elsewhere in this conference. 15 A signal template for the on-axis conditions was generated using the grayscale images after transforming them to luminance with the standard display function defined in DICOM Part 14 (which was also applied in the observer study). Another template for the off-axis conditions was created similarly after resampling the grayscale images horizontally by a factor of sin(45 deg) to simulate the off-axis appearance of those images.…”

Section: Methodsmentioning

confidence: 99%

Channelized model observer using a visual discrimination model

Johnson

Lubin²,

Nafziger³

et al. 2005

SPIE Proceedings

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Previous studies in which the JNDmetrix visual discrimination model (VDM) was applied to predict effects of image display and processing factors on lesion detectability have shown promising results for mammographic images with microcalcification clusters. In those studies, just-noticeable-difference (JND) metrics were computed for signal-present and signal-absent image pairs with the same background. When this "paired discriminability" method was applied to Gaussian signals in 1/f 3 filtered noise, however, it was unable to predict detection thresholds measured in 2AFC trials for different backgrounds. We suggested previously (SPIE 2002) that a statistical model observer using channel responses from "single-ended" VDM simulations could predict detection performance with different backgrounds. The implementation and evaluation of that VDM-channelized model observer is described in this paper. Model performance was computed for sets of signal and noise images from two observer performance studies involving the detection of simulated or real breast masses. For the first study, the VDM-channelized model observer was able to predict the dependence of detection thresholds on signal size (contrast-detail slope) for 2AFC detection of Gaussian signals on different 1/f 3 noise backgrounds. Variations in the detectability of masses in mammograms from the second study correlated well with model performance as a function of display type (LCD vs. CRT) and viewing angle (on-axis vs. 45° off-axis). The performance of the VDM-channelized model observer was superior to results obtained using either the VDM paired discriminability method or a conventional nonprewhitening model observer.

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Section: Methodsmentioning

confidence: 99%

Channelized model observer using a visual discrimination model

Johnson

Lubin²,

Nafziger³

et al. 2005

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently we studied the effects on performance for viewing images on CRTs and LCDs on and off axis -since LCD displays have significant degradation in image quality as one views from any non-orthogonal position. 8 We found that the paired discrimination version of the model that we had used previously was able to predict correctly performance in the on-axis viewing condition but not in the off-axis condition. We therefore modified the model to a channelized version, taking more properties of the human visual system into account and found that we were able to predict successfully performance in both conditions.…”

Section: Introductionmentioning

confidence: 93%

Model prediction of just noticeable differences: Are the eyes attracted to the same areas?

et al. 2005

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The JNDmetrix human visual system model developed by the Sarnoff Corporation is used to predict observer performance on visual discrimination tasks. It begins with two paired images as the initial input and ends with a JND map that shows the magnitude and spatial location of visible differences between the two input images. The goal of this experiment was to determine if the location and magnitude of JNDs identified by the model corresponded to visual search parameters of the human observer. Radiologists searched 20 mammograms with multiple masses and microcalcifications of different subtleties as their eye-position was recorded. The JNDmetrix model analyzed the same images and identified, with JNDs, discriminable areas on the images. Lesions with lower subtlety ratings were detected later in search than more obvious ones (FNs later than TPs). When the subtler lesions were detected (TP) dwell time was longer than more obvious lesions, but the FNs received shorter total dwell. The subtler lesions when detected (TP) received more total fixation clusters than more obvious ones, but the FNs received fewer. The correlation between the model JNDs and the eye-position parameters was high. Understanding the influence of lesion subtlety on search may help us better model and predict human observer performance.

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Viewing images on and off axis with CRT and LCD monitors: effects on observer and model performance

Cited by 2 publications

References 16 publications

Channelized model observer using a visual discrimination model

Channelized model observer using a visual discrimination model

Model prediction of just noticeable differences: Are the eyes attracted to the same areas?

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