Lung Tuberculosis (TB) remains a critical health issue globally. Accurately detecting TB from chest x-rays is vital for prompt diagnosis and treatment. Our study introduces an innovative approach using the swin transformer to assist healthcare professionals in making faster, more accurate diagnoses. This method also aims to lower diagnostic costs by streamlining the detection process. The swin transformer, a sophisticated vision transformer, leverages hierarchical feature representation and a shifted window mechanism for improved image Analysis.