Digital imaging provides an effective means to electronically acquire, archive, distribute, and view medical images. Medical imaging display stations are an integral part of these operations. Therefore, it is vitally important to assure that electronic display devices do not compromise image quality and ultimately patient care. The AAPM Task Group 18 (TG18) recently published guidelines and acceptance criteria for acceptance testing and quality control of medical display devices. This paper is an executive summary of the TG18 report. TG18 guidelines include visual, quantitative, and advanced testing methodologies for primary and secondary class display devices. The characteristics, tested in conjunction with specially designed test patterns (i.e., TG18 patterns), include reflection, geometric distortion, luminance, the spatial and angular dependencies of luminance, resolution, noise, glare, chromaticity, and display artifacts. Geometric distortions are evaluated by linear measurements of the TG18-QC test pattern, which should render distortion coefficients less than 2%/5% for primary/secondary displays, respectively. Reflection measurements include specular and diffuse reflection coefficients from which the maximum allowable ambient lighting is determined such that contrast degradation due to display reflection remains below a 20% limit and the level of ambient luminance (Lamb) does not unduly compromise luminance ratio (LR) and contrast at low luminance levels. Luminance evaluation relies on visual assessment of low contrast features in the TG18-CT and TG18-MP test patterns, or quantitative measurements at 18 distinct luminance levels of the TG18-LN test patterns. The major acceptable criteria for primary/ secondary displays are maximum luminance of greater than 170/100 cd/m2, LR of greater than 250/100, and contrast conformance to that of the grayscale standard display function (GSDF) of better than 10%/20%, respectively. The angular response is tested to ascertain the viewing cone within which contrast conformance to the GSDF is better than 30%/60% and LR is greater than 175/70 for primary/secondary displays, or alternatively, within which the on-axis contrast thresholds of the TG18-CT test pattern remain discernible. The evaluation of luminance spatial uniformity at two distinct luminance levels across the display faceplate using TG18-UNL test patterns should yield nonuniformity coefficients smaller than 30%. The resolution evaluation includes the visual scoring of the CX test target in the TG18-QC or TG18-CX test patterns, which should yield scores greater than 4/6 for primary/secondary displays. Noise evaluation includes visual evaluation of the contrast threshold in the TG18-AFC test pattern, which should yield a minimum of 3/2 targets visible for primary/secondary displays. The guidelines also include methodologies for more quantitative resolution and noise measurements based on MTF and NPS analyses. The display glare test, based on the visibility of the low-contrast targets of the TG18-GV test pattern or...

Existing methods for image contrast enhancement focus mainly on the properties of the image to be processed while excluding any consideration of the observer characteristics. In several applications, particularly in the medical imaging area, effective contrast enhancement for diagnostic purposes can be achieved by including certain basic human visual properties. Here the authors present a novel adaptive algorithm that tailors the required amount of contrast enhancement based on the local contrast of the image and the observer's Just-Noticeable-Difference (JND). This algorithm always produces adequate contrast in the output image, and results in almost no ringing artifacts even around sharp transition regions, which is often seen in images processed by conventional contrast enhancement techniques. By separating smooth and detail areas of an image and considering the dependence of noise visibility on the spatial activity of the image, the algorithm treats them differently and thus avoids excessive enhancement of noise, which is another common problem for many existing contrast enhancement techniques. The present JND-Guided Adaptive Contrast Enhancement (JGACE) technique is very general and can be applied to a variety of images. In particular, it offers considerable benefits in digital radiography applications where the objective is to increase the diagnostic utility of images. A detailed performance evaluation together with a comparison with the existing techniques is given to demonstrate the strong features of JGACE.

The use of color LCDs in medical imaging is growing as more clinical specialties use digital images as a resource in diagnosis and treatment decisions. Telemedicine applications such as telepathology, teledermatology, and teleophthalmology rely heavily on color images. However, standard methods for calibrating, characterizing, and profiling color displays do not exist, resulting in inconsistent presentation. To address this, we developed a calibration, characterization, and profiling protocol for color-critical medical imaging applications. Physical characterization of displays calibrated with and without the protocol revealed high color reproduction accuracy with the protocol. The present study assessed the impact of this protocol on observer performance. A set of 250 breast biopsy virtual slide regions of interest (half malignant, half benign) were shown to six pathologists, once using the calibration protocol and once using the same display in its "native" off-the-shelf uncalibrated state. Diagnostic accuracy and time to render a decision were measured. In terms of ROC performance, Az (area under the curve) calibrated = 0.8570 and Az uncalibrated = 0.8488. No statistically significant difference (p = 0.4112) was observed. In terms of interpretation speed, mean calibrated = 4.895 s; mean uncalibrated = 6.304 s which is statistically significant (p = 0.0460). Early results suggest a slight advantage diagnostically for a properly calibrated and color-managed display and a significant potential advantage in terms of improved workflow. Future work should be conducted using different types of color images that may be more dependent on accurate color rendering and a wider range of LCDs with varying characteristics.

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A major issue in telepathology is the extremely large and growing size of digitized “virtual” slides, which can require several gigabytes of storage and cause significant delays in data transmission for remote image interpretation and interactive visualization by pathologists. Compression can reduce this massive amount of virtual slide data, but reversible (lossless) methods limit data reduction to less than 50%, while lossy compression can degrade image quality and diagnostic accuracy. “Visually lossless” compression offers the potential for using higher compression levels without noticeable artifacts, but requires a rate-control strategy that adapts to image content and loss visibility. We investigated the utility of a visual discrimination model (VDM) and other distortion metrics for predicting JPEG 2000 bit rates corresponding to visually lossless compression of virtual slides for breast biopsy specimens. Threshold bit rates were determined experimentally with human observers for a variety of tissue regions cropped from virtual slides. For test images compressed to their visually lossless thresholds, just-noticeable difference (JND) metrics computed by the VDM were nearly constant at the 95th percentile level or higher, and were significantly less variable than peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics. Our results suggest that VDM metrics could be used to guide the compression of virtual slides to achieve visually lossless compression while providing 5–12 times the data reduction of reversible methods.