title: Detection of Pneumonia in chest X-ray images.
abstract: Pneumonia is the common type of infection found in the world. The infection spreads in the lungs area of a human body. The chest x-ray is performed to diagnose this infection. Physicians use this X-ray image to diagnose or monitor treatment for conditions of pneumonia. This type of chest X-ray is also used in the diagnosis of diseases like emphysema, lung cancer, line and tube placement and tuberculosis. Feature extraction methods like DWT, WFT, and WPT can also be used. In this paper, detection of pneumonia infection by unsupervised fuzzy c-means classification learning algorithm is used. This approach gives better result than the rest of the methods. In fuzzy c-means, each resultant pixel gives accurate value since it has a weight associated with it.
authors.affiliation: Department of MCA, K.L.N. College of Engineering, Pottapalayam, Madurai, India.
authors.forename: N Ravia Shabnam
authors.initials: NR
authors.lastname: Parveen
authors.affiliation: Sadakathullah Appa College, Tirunelveli, India.
authors.forename: M Mohamed
authors.initials: MM
authors.lastname: Sathik
mesh_terms: D016000:Cluster Analysis; D017143:Fuzzy Logic; D006801:Humans; D011014:Pneumonia / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*
keywords: Feature extraction; fuzzy c-means classification; pneumonia; unsupervised learning