X線画像の信号検出と視覚特性の重要性

Abstract

Observer performance experiments using ROC analysis indicated that the detectability of subtle microcalcifications in digitized mammograms was improved by unsharp-mask filtering. However, the processed mammograms still provided lower accuracy than the original mammogram. Similar studies with mild interstitial infiltrates and subtle pneumothoraces in chest radiographs showed that the use of a pixel size substantially larger than 0.1 mm may result in some loss of diagnostic accuracy, and that a 2048×2048 matrix may be a satisfactory compromise for digital chest radiography. The unsharp masking may improve diagnostic accuracy for pneumothorax, while radiologists' performance in identifying interstitial infiltrates was degraded by the image processing. The contrast-detail (C-D) diagram was measured by using simulated square patterns superimposed on radiographic noise. Experimental variations in conventional C-D curves due to observer differences, within-reader variability, and image noise outcomes were quite large, and therefore it was necessary to increase the total number of observations in order to obtain reliable results. The relationship between physical and visual image quality for the task of detecting plastic beads was studied on thirty-seven different radiographic imaging conditions using a 2AFC visual detection experiment. Results indicated that human observer detection performance most closely resembled that of a sub-optimal statistical decision process. The effects of imaging and display conditions on the detectability of low-contrast objects in DSA images were investigated by using 18AFC experiments. We found that the SNR obtained from the perceived statistical decision theory model, which includes the observer's internal noise, can accurately predict the detectability of low-contrast objects in DSA images. The effect of pixel size on the SNR and threshold detection of low-contrast radiologic pattern was investigated theoretically for digital radiographic systems. No substantial difference between 0.1 and 0.2 mm pixel sizes was found in threshold contrasts for square objects. No substantial difference between 0.1 and 0.2 mm pixel sizes was found in threshold contrasts for square objects ranging from 0.1 to 20 mm, and thus we conclude that 0.2 mm pixel would be sufficiently small for visualization of most image detail in many radiologic examinations. The effects of image processing with unsharp masking, Metz filters, matched filters and optimal statistical filter on the detection of simulated square objects superimposed on radiographic mottle were studied theoretically and experimentally. The usefulness and limitations of these filters were discussed.