Exploiting Cascaded Ensemble of Features for the Detection of Tuberculosis Using Chest Radiographs

نویسندگان

چکیده

Tuberculosis (TB) is a communicable disease that one of the top 10 causes death worldwide according to World Health Organization. Hence, Early detection an important task save millions lives from this life threatening disease. For diagnosing TB chest X-Ray, different handcrafted features were utilized previously and they provided high accuracy even in small dataset. However, at present, deep learning (DL) gains popularity many computer vision tasks because their better performance comparison traditional manual feature extraction based machine approaches not exception. Considering all these facts, cascaded ensembling method proposed combines both hand-engineered learning-based for task. To make model more generalized, rotation-invariant augmentation techniques are introduced which found very effective By using method, outstanding achieved through extensive simulation on two benchmark datasets (99.7% 98.4% Shenzhen Montgomery County respectively) verifies effectiveness method.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2021

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2021.3102077