Detection of Overlapping Tuberculosis Bacilli in Sputum Smear Images

Abstract

Tuberculosis (TB) is a common and lethal infectious disease caused by a germ (bacterium) called Mycobacterium tuberculosis. Early diagnosis of the disease is one of the primary challenges in curtailing its spread and is a critical step in the TB-Control Program worldwide. Among the most common methods used in the diagnosis of TB is the manual microscopic examination of a ZN-stained sputum smear which is a time-consuming and error-prone process. The diagnosis crucially depends on the number of viable or dormant mycobacteria in the sputum, which are seen as red colored rod-shaped objects in the smear under a microscope. This also means that the mycobacteria have to be detected accurately in order to arrive at the correct count, the accuracy of which could be affected when there are overlapping bacilli in the images. The use of Image Analysis in the detection of the mycobacteria will introduce a paradigm shift. The proposed work identifies such overlapping mycobacteria and uses techniques to total them accurately, which is an extension of an earlier work focusing only on segmentation of the tiny organisms. Normal bacilli are just 2-4 micrometers in length and 0.2-0.5 um in width. All the organisms that fall above their average size or show a variation in the ratio of the major-to-minor axis are identified to be overlapping mycobacteria, which are then used for further analysis. The count of mycobacteria that overlap is computed by obtaining the branch points in the skeleton of the overlapping object. The dataset used in the research consisted of eighty images, which were tested using a prototype application that achieved a success rate of 70%.