The problem of estimating the parameter ?, when it is restricted to an interval of the form , in a class of discrete distributions, including Binomial Negative Binomial discrete Weibull and etc., is considered. We give necessary and sufficient conditions for which the Bayes estimator of with respect to a two points boundary supported prior is minimax under squared log error loss function....

abstract background: a computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   materials and methods: the per­formance of the artificial neural network (ann) was evaluated us...

introduction: one of the major causes of image non-uniformity in mri is due to the existence of  non-homogeneity in rf receive and transmit. this can be the most effective source of error in  quantitative  studies  in  mri  imaging.  part  of  this  non-homogeneity  demonstrates  the  characteristics of rf coil and part of it is due to the interaction of rf field with the material being  imaged...

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Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by these results, researchers have looked to overcome naive Bayes’ primary weakness—attribute independence—and improve the performance of the algorithm. This paper presents a locally weighted version of naive Bayes that relaxe...

We present a new algorithm for the feature-space based segmentation of medical image volumes, based on a unified mathematical framework that incorporates both intensity and local gradient information. The algorithm addresses the problem of partial volume tissue estimation and is capable of using multiple image volumes, and the associated multi-dimensional image gradient, to increase tissue sepa...