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What is Automated TB Detection Using Adaboost about?

The document describes an automatic tuberculosis detection system using CT lung images. It uses five stages: pre-processing, segmentation, feature extraction, feature selection, and classification. Wavelet-based texture features are extracted and optimal features selected using genetic algorithm. An Adaboost classifier is used for classification, achieving 93% accuracy in distinguishing TB affected and non-affected lungs. The system aims to improve on existing TB detection methods by automating diagnosis fr

Author

mahima 008

Language

EN