Detection of protein conformation defects from fluorescence microscopy images

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@Article{Guo:2013:EAAI,

• author = "Peifang Guo and Prabir Bhattacharya",
• title = "Detection of protein conformation defects from fluorescence microscopy images",
• journal = "Engineering Applications of Artificial Intelligence",
• volume = "26",
• number = "8",
• pages = "1936--1941",
• year = "2013",
• ISSN = "0952-1976",
• DOI = "doi:10.1016/j.engappai.2013.05.007",
• URL = "http://www.sciencedirect.com/science/article/pii/S0952197613000948",
• keywords = "genetic algorithms, genetic programming, EM, Pattern classification, Computer-aided diagnosis, Protein conformational diseases, Histogram, Microscopic images, Texture analysis",
• abstract = "A diagnostic method for protein conformational diseases (PCD) from microscopy images is proposed when such conformational conflicts involve muscular intra-nuclear inclusions (INIs) indicative of oculopharyngeal muscular dystrophy (OPMD), one variety of PCD. The method combines two techniques: (1) the Histogram Region of Interest Fixed by Thresholds (HRIFT) is designed to capture the colour information of INIs for basic feature extraction; (2) an automated feature synthesis, based on the HRIFT features, is designed to identify OPMD by means of Genetic Programming and the Expectation Maximisation algorithm (GP-EM) for classification improvement. With variations in size, shape, and background structure, a total of 600 microscopic images are analysed for the binary classes of healthy and sick conditions of OPMD. The integrated technique of the approach reveals a sensitivity of 0.9 and an area of 0.961 under the receiver operating characteristic (ROC) at a specificity of 0.95. Furthermore, significant improvements in classification accuracy and computational time are demonstrated by comparison with other methods.",

}

Genetic Programming entries for Pei Fang Guo Prabir Bhattacharya

Citations