SMO-based System for Identifying Common Lung Conditions Using Histogram
2013 7th International Symposium on Medical Information and Communication Technology (ISMICT)
A radiograph is a visualization aid that physicians use in identifying lung abnormalities. Although digitized x-ray images are available, diagnosis by a medical expert through pattern recognition is done manually. Thus, this paper presents a system that utilizes machine learning for pattern recognition and classification of three lung conditions, namely Normal, Pleural Effusion and Pneumothorax cases. Using two histogram equalization techniques, the designed system achieves an accuracy rate of 76.19% and 78.10% by using Sequential Minimal Optimization (SMO).
de la Cruz, R. G., Roque, T. C., Rosas, J. G., Vera Cruz, C. M., Cordel II, M. O., Ilao, J. P., Rabe, A. J., & Parungao, Jr., P. J. (2013). SMO-based System for Identifying Common Lung Conditions Using Histogram. 2013 7th International Symposium on Medical Information and Communication Technology (ISMICT), 112-116. 10.1109/ISMICT.2013.6521711