期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2019
卷号：7
期号：3
页码：1962-1968
DOI：10.15680/IJIRCCE.2019. 0703071
出版社：S&S Publications
摘要：Tuberculosis (TB) disease is a main global health threat. An estimated one-third of the world’s
population has been exposed to TB, and millions of new infections are occurring every year. Tuberculosis naturally
affects the lungs it also affects the other parts of our body. Tuberculosis is currently the world's leading cause of death
from a single infectious disease. In the case of an epidemic the only option of diagnosis remains is the sputum
examination. Tuberculosis is most common contagious disease. Nowadays, millions of human beings of the world are
suffering from it. To improve the diagnostic process we are developing an automated method for the detection of
tuberculosis bacilli in clinical specimens, preferably sputum smears. The main constraints are expertise human, time
and cost to implement our process. We will use Thresholding, multi-stage, SVD segmentation identified possible
‘Tuberculosis objects’, removed artifacts by shape comparison and color-labeled objects as ‘definite’, ‘possible’ or
‘non-Tuberculosis’, bypassing photomicrography calibration. In our work, we will use an algorithm based on image
processing is developed for identification of Tuberculosis. The developed system , currently shows 93.5% sensitivity
for identifying individual bacilli. There are numerous TB bacilli with active pulmonary TB in the patient's sputum. The
overall diagnostic accuracy of the patients with positive smear is expected to be very high. Some potential benefits of
automated screening for TB are accurate and rapid diagnosis, increased population screening and reduced health risk.
