The detection of crackles based on mathematical morphology in spectrogram analysis.

BACKGROUND Crackles are very common abnormal breath sounds in the lung and can be used to diagnose pulmonary diseases. OBJECTIVE In this study, a method is proposed for the detection of adventitious transient sounds from normal breath sounds. METHODS This method automatically recognizes crackles based on the extraction and analysis of spectral information from digitally recorded lung sounds. Various mathematical morphology feature sets were extracted through wavelet spectrogram analysis on pulmonary signals. In order to evaluate the effects of different wavelets types on crackle detection, different wavelets were tested. RESULTS The results showed that the proposed method achieved an 86% accuracy in the detection of crackles. CONCLUSIONS The spectrograms of the crackles in the lung exhibit irregular ellipse image features. For lung sound analysis, this is a useful feature that can be used for the immediate recognition and analysis of crackles.