Comparison of grayscale and color-scale renderings of digital medical images for diagnostic interpretation.

Medical images are increasingly being rendered as digital images that are displayed on a monitor to provide diagnoses. However, these images are often rendered in grayscale. In this context, we compare the detectability of low-contrast signals between digital grayscale images and color-scale images. Low-contrast phantom images were rendered with the use of five color tables (gray, blue, red, yellow, and green). The 32 acquired images sorted in random order were evaluated by nine observers, and their observations were subjected to receiver operating characteristic analysis. In addition, the evaluators' preferred color and their eye fatigue upon image observation were compared. The low-contrast resolutions of yellow and green color scales were superior to that of grayscale. The use of yellow resulted in the least eye fatigue, and importantly our results indicate that the interpretation of digital medical images can be improved when these images are rendered in a "yellow scale" rather than grayscale.

[Development of a digital chest phantom for studies on energy subtraction techniques].

Digital chest phantoms continue to play a significant role in optimizing imaging parameters for chest X-ray examinations. The purpose of this study was to develop a digital chest phantom for studies on energy subtraction techniques under ideal conditions without image noise. Computed tomography (CT) images from the LIDC (Lung Image Database Consortium) were employed to develop a digital chest phantom. The method consisted of the following four steps: 1) segmentation of the lung and bone regions on CT images; 2) creation of simulated nodules; 3) transformation to attenuation coefficient maps from the segmented images; and 4) projection from attenuation coefficient maps. To evaluate the usefulness of digital chest phantoms, we determined the contrast of the simulated nodules in projection images of the digital chest phantom using high and low X-ray energies, soft tissue images obtained by energy subtraction, and "gold standard" images of the soft tissues. Using our method, the lung and bone regions were segmented on the original CT images. The contrast of simulated nodules in soft tissue images obtained by energy subtraction closely matched that obtained using the gold standard images. We thus conclude that it is possible to carry out simulation studies based on energy subtraction techniques using the created digital chest phantoms. Our method is potentially useful for performing simulation studies for optimizing the imaging parameters in chest X-ray examinations.