Selecting a variable for predicting the diagnosis of PTB patients from comparison of chest X-ray images

Abstract

A statistical method of comparing two digital chest radiographs for Pulmonary Tuberculosis (PTB) patients has been proposed. After applying appropriate image registration procedures, a selected subset of each image is converted to an image histogram (or box plot). Comparing two chest X-ray images is equivalent to the direct comparison of the two corresponding histograms. From each histogram, eleven percentiles (of image intensity) are calculated. The number of percentiles that shift to the left (NLSP) when second image is compared to the first has been shown to be an indicator of patients' progress. In this study, the values of NLSP is to be compared with the actual diagnosis (Y) of several medical practitioners. A logistic regression model is used to study the relationship between NLSP and T. This study showed that NLSP may be used as an alternative or second opinion for Y. The proposed regression model also show that important explanatory variables such as outcomes of sputum test (Z) and degree of image registration (W) may be omitted when estimating Y-values.