Detection of sputum by interpreting the time-frequency distribution of respiratory sound signal using image processing techniques | Zendy

Jinglong Niu | Zendy; Yan Shi | Zendy; Maolin Cai | Zendy; Zhixin Cao | Zendy; Dandan Wang | Zendy; Zhaozhi Zhang | Zendy; Xiaohua Douglas Zhang | Zendy

Open Access

Detection of sputum by interpreting the time-frequency distribution of respiratory sound signal using image processing techniques

Author(s) -

Jinglong Niu,

Yan Shi,

Maolin Cai,

Zhixin Cao,

Dandan Wang,

Zhaozhi Zhang,

Xiaohua Douglas Zhang

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx652

Subject(s) - sputum , preprocessor , computer science , matlab , sound (geography) , pattern recognition (psychology) , feature extraction , artificial intelligence , feature (linguistics) , speech recognition , medicine , pathology , acoustics , tuberculosis , physics , linguistics , philosophy , operating system

Sputum in the trachea is hard to expectorate and detect directly for the patients who are unconscious, especially those in Intensive Care Unit. Medical staff should always check the condition of sputum in the trachea. This is time-consuming and the necessary skills are difficult to acquire. Currently, there are few automatic approaches to serve as alternatives to this manual approach.

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