Tuberculosis (TB) Is An Airborne Infectious Disease Caused By Organisms In The Mycobacterium Tuberculosis (Mtb) Complex. In Many Low And Middle-income Countries, TB Remains A Major Cause Of Morbidity And Mortality. Once A Patient Has Been Diagnosed With TB, It Is Critical That Healthcare Workers Make The Most Appropriate Treatment Decision Given The Individual Conditions Of The Patient And The Likely Course Of The Disease Based On Medical Experience. Depending On The Prognosis, Delayed Or Inappropriate Treatment Can Result In Unsatisfactory Results Including The Exacerbation Of Clinical Symptoms, Poor Quality Of Life, And Increased Risk Of Death. The Advent Of Digital Chest Radiography And The Possibility Of Digital Image Processing Has Given New Impetus To Computeraided Screening And Diagnosis. This System Present An Automated Approach For Detecting TB Manifestations In Chest X-rays (CXRs), Based Earlier Work In Lung Segmentation And Lung Disease Classification. In An Effort To Reduce The Burden Of The Disease, Automated Approach For Detecting Tuberculosis In Conventional Posteroanterior Chest Radiographs
