Image feature analysis and computer-aided diagnosis in digital radiography: Effect of digital parameters on the accuracy of computerized analysis of interstitial disease in digital chest radiographs

Abstract

We are developing a computerized method for measurement of lung texture in digital chest radiographs for detection and characterization of intestinal disease. Physical texture measures are obtained from analysis of the power spectrum of the lung texture. We have investigated the effect of digital parameters such as pixel size, regions of interest size, the number of quantization levels, and the peak frequency of the visual system response, as well as the effect of the unsharp masking technique on the performance of this computerized method. We calculated the texture measures by changing digital parameters for 100 normal lungs and 100 abnormal lungs in our database. Receiver operating characteristic (ROC) curves were employed for evaluation of the performance of this computerized method for distinguishing between normal and abnormal lungs. We used the area under the ROC curve to compare the detection accuracy for interstitial infiltrates. We believe that the results of this study may be useful as a guide in the design of computerized schemes for lung texture analysis in digital chest radiographs.