John S. Nafziger

Use of a Human Visual System Model to Predict Observer Performance with CRT vs LCD Display of Images

This Project evaluated a human visual system model (JNDmetrix) based on just noticeable difference (JND) and frequency-channel vision-modeling principles to assess whether a Cathode ray tube (CRT) or a liquid crystal display (LCD) monochrome display monitor would yield better observer performance in radiographic interpretation. Key physical characteristics, such as veiling glare and modulation transfer function (MTF) of the CRT and LCD were measured. Regions of interest from mammographic images with masses of different contrast levels were shown once on each display to six radiologists using a counterbalanced presentation order. The images were analyzed using the JNDmetrix model. Performance as measured by receiver operating characteristic (ROC) analysis was significantly better overall on the LCD display (P = 0.0120). The JNDmetrix model predicted the result (P = 0.0046) and correlation between human and computer observers was high (r2 (quadratic) = 0.997). The results suggest that observer performance with LCD displays is superior to CRT viewing, at least for on-axis viewing.

Visual discrimination modeling of lesion detectability

The Sarnoff JNDmetrix visual discrimination model (VDM) was applied to predict human psychophysical performance in the detection of simulated mammographic lesions. Contrast thresholds for the detection of synthetic Gaussian masses on mean backgrounds and simulated mammographic backgrounds were measured in two-alternative, forced-choice (2AFC) trials. Experimental thresholds for 2-D Gaussian signal detection decreased with increasing signal size on mean backgrounds and on 1/f3 filtered noise images presented with identical (paired) backgrounds. For 2AFC presentations of different (unpaired) filtered noise backgrounds, detection thresholds increased with increasing signal diameter, consistent with a decreasing signal-to-noise ratio. Thresholds for mean and paired filtered noise backgrounds were used to calibrate a new low-pass, spatial-frequency channel in the VDM. The calibrated VDM was able to predict accurate detection thresholds for Gaussian signals on mean and paired 1/f3 filtered noise backgrounds. To simulate noise-limited detection thresholds for unpaired backgrounds, an approach is outlined for the development of a VDM-based model observer based on statistical decision theory.

Effects of surround motion on receptive-field gain and structure in area 17 of the cat.

Modulation of responses elicited by moving bars within the classical receptive fields (CRF) of cat area 17 neurons were studied as a function of the direction and velocity of drifting gratings in the surrounds. Several different types of modulation were observed; collectively, the responses of most cells, both simple and complex, were strongly modulated by surround motion. None of these cells appear to signal relative velocity between the CRF and its surround. The gain and spatiotemporal structure of the CRF mechanism were estimated using contrast-response functions and reverse correlation with spatiotemporal ternary white noise, respectively. These measurements were made in the presence of surround gratings shown to significantly modify responses elicited from the CRF. In all cases, the gain of the CRF mechanism was driven up or down relative to controls but the receptive-field structure did not change in any way. We conclude that neurons in cat area 17 act like scalable filters, meaning that their gains can be adjusted by stimuli in the surrounds without altering the properties of the CRF. This was verified by showing that velocity tuning curves were also unmodified by stimuli in the surround that did change the gain. Based in part on these data, we discuss the notion that primary visual cortex makes use of a double-opponent mechanism for the representation of local discontinuities in motion and orientation.

Perceptually optimized compression of mammograms

The Sarnoff JNDmetrix visual discrimination model (VDM) was applied to predict the visibility of compression artifacts in mammographic images. Sections of digitized mammograms were subjected to irreversible (lossy) JPEG and JPEG 2000 compression. The detectability of compressed images was measured experimentally and compared with VDM metrics and PSNR for the same images. Artifacts produced by JPEG 2000 compression were generally easier for observers to detect than those produced by JPEG encoding at the same compression ratio. Detection thresholds occurred at JPEG 2000 compression ratios from 6:1 to 10:1, significantly higher than the average 2:1 ratio obtained for reversible (lossless) compression. VDM predictions of artifact visibility were highly correlated with observer performance for both encoding techniques. Performance was less correlated with encoder bit rate and PSNR, which was a relatively poor predictor of threshold bit rate across images. Our results indicate that the VDM can be used to predict the visibility of compression artifacts and guide the selection of encoder bit rate for individual images to maintain artifact visibility below a specified threshold.

Use of a Human Visual System Model to Predict the Effects of Display Veiling Glare on Observer Performance

The goal of this project was to evaluate a human visual system model (JNDmetrix) based on JND and frequency-channel vision-modeling principles to predict the effects of monitor veiling glare on observer performance in interpreting radiographic images. The veiling glare of a high-performance CRT and an LCD display was measured. A series of mammographic images with masses of different contrast levels was generated. Six radiologists viewed the sets of images on both monitors and reported their decision confidence about the presence of a mass. The images were also run through the JNDmetrix model. Veiling glare affected observer performance (ROC Az). Performance was better on the LCD display with lower veiling glare compared to the CRT with higher veiling glare. The JNDmetrix model predicted the same pattern of results and the correlation between human and computer observers was high. Veiling glare can affect significantly observer performance in diagnostic radiology. A possible confound exists in that two different monitors were used and other physical parameters may contribute to the differences observed. A new set of studies is underway to remove that confound.

Visual image quality metrics for optimization of breast tomosynthesis acquisition technique

Breast tomosynthesis is currently an investigational imaging technique requiring optimization of its many combinations of data acquisition and image reconstruction parameters for optimum clinical use. In this study, the effects of several acquisition parameters on the visual conspicuity of diagnostic features were evaluated for three breast specimens using a visual discrimination model (VDM). Acquisition parameters included total exposure, number of views, full resolution and binning modes, and lag correction. The diagnostic features considered in these specimens were mass margins, microcalcifications, and mass spicules. Metrics of feature contrast were computed for each image by defining two regions containing the selected feature (Signal) and surrounding background (Noise), and then computing the difference in VDM channel metrics between Signal and Noise regions in units of just-noticeable differences (JNDs). Scans with 25 views and exposure levels comparable to a standard two-view mammography exam produced higher levels of feature contrast. The effects of binning and lag correction on feature contrast were found to be generally small and isolated, consistent with our visual assessments of the images. Binning produced a slight loss of spatial resolution which could be compensated in the reconstruction filter. These results suggest that good image quality can be achieved with the faster and therefore more clinically practical 25-view scans with binning, which can be performed in as little as 12.5 seconds. Further work will investigate other specimens as well as alternate figures of merit in order to help determine optimal acquisition and reconstruction parameters for clinical trials.

Visually lossless compression of breast biopsy virtual slides for telepathology

A major issue in telepathology is the extreme size of digitized slides, which require several gigabytes of storage and cause significant delays in image delivery to pathologists. We investigated the utility of a visual discrimination model (VDM) to predict bit rates for visually lossless JPEG2000 compression of breast biopsy virtual slides. Visually lossless bit rates were determined experimentally with human observers. VDM metrics computed for those bit rates were nearly constant, suggesting that VDMs could be used to achieve visually lossless image quality while providing about four times the data reduction of reversible compression.

Assessment of the influence of display veiling glare on observer and model performance

We evaluated human observer and model (JNDmetrix) performance to assess whether the veiling glare of a digital display influences performance in softcopy interpretation of mammographic images. 160 mammographic images, half with a single mass, were processed to simulate four levels of veiling glare: none, comparable to a typical cathode ray tube (CRT) display, double a CRT and quadruple a CRT. Six radiologist observers were shown the images in a randomized presentation order on a liquid crystal display (LCD) that had relatively no veiling glare. The JNDmetrix human visual system model also analyzed the images. Receiver Operating Characteristic (ROC) techniques showed that performance declined with increasing veiling glare (F = 6.884, p = 0.0035). Quadruple veiling glare yielded significantly lower performance than the lower veiling glare levels. The JNDmetrix model did not predict a reduction in performance with changes in veiling glare, and correlation with the human observer data was modest (0.588). Display veiling glare may influence observer performance, but only at very high levels.

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

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.

Effects of visual fixation cues on the detectability of simulated breast lesions

A discrepancy exists between two studies that investigated psychophysical detection of simulated lesions (e.g. gaussians or designer nodules) embedded in filtered noise images (Johnson et al, 2002; Burgess et al, 2003). Johnson et al, 2002 identified a significant difference in the slope of the contrast detail plots (CD plots) as the presentation methodology in a 2AFC task was changed from the unlike background (unpaired) to identical backgrounds (paired). In comparable experiments, Burgess et al, 2003 challenged the results by finding no difference between the slopes (both positive) of the CD plots when using paired backgrounds or unpaired backgrounds. We found that a significant difference between the two studies, namely the presence of a circular fixation cue was responsible for the discrepancy. The detection noise due to positional uncertainty was sufficient to reduce subjects threshold for small target diameters. This effect was amplified in the paired background, switching the CD plot from a negative slope (without fixation) to a positive slope (with fixation). The effect was less dramatic with the unpaired backgrounds, however intra-observer variability seemed to be reduced with fixation cues. These results significantly reduce the discrepancies in C-D characteristics between the two studies.