出版社：Defence Scientific Information & Documentation Centre
摘要：The statistical characterisation of gray level distribution of echocardiographic images is commonly done in terms of unimodal probability densities such as Rayleigh, Gamma, Weibull, Nakagami, and Lognormal. Amongst these distributions, the Gamma density is found to provide better empirical model that fits to real data sets. We propose to extend the class of probability distributions by exploring Pearson family to characterise blood and tissue in echocardiographic images. It is found that Pearson Type I characterises the tissue regions whereas Type I, Type IV and Type VI classify blood regions. The statistical measures viz. Jensen-Shannon (JS) divergence and Kolmogorov-Smirnov (KS) statistics reveal that Pearson family of curves outperforms the Gamma distribution. Defence Science Journal, 2011, 61(5), pp.473-478 , DOI:http://dx.doi.org/10.14429/dsj.62.1163
