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In mammography diagnosis systems, high False Negative Rate (FNR) has always been a significant problem since a false negative answer may lead to a patient's death. This paper is directed towards the development of a novel Computer-aided Diagnosis (CADx) system for the diagnosis of breast masses. It aims at intensifying the performance of CADx algorithms as(More)
The power-delay product is a direct measurement of the energy expanded per operational cycle of an arithmetic circuit. Lowering the supply voltage of the full adder cell to achieve low power-delay product is a sensible approach to improve the power efficiency at sustainable speed of arithmetic circuits composed of such instances at high level design. In(More)
Classification of breast abnormalities such as masses is a challenging task for radiologists. Computer-aided Diagnosis (CADx) technology may enhance the performance of radiologists by assisting them in classifying patterns into benign and malignant categories. Although Neural Networks (NN) such as Multilayer Perceptron (MLP) have drawbacks, namely long(More)
To compensate for bias field inhomogeneity and reduce noise, we incorporate domain-based knowledge and spatial information into a brain segmentation algorithm by proposing a new multi-layer Hidden Markov model. Brain tissues include Gray Matter (GM), White Matter (WM), and Cerebrospinal Fluid (CSF). A typical slice of a brain image either contains GM, GM-WM(More)
Rosette pattern scanning is a method of scanning in a space of field of view (FOV), so that an entire surface can be scanned by the rosette pattern model. Regarding the nonlinearity of rosette patterns, there are complicated calculations. We can map rosette pattern space to a two-dimensional space called RMA. In this space, nonlinearity effects of rosette(More)
Image registration is an important issue in medical analysis. In this process the spatial transformation that aligns the reference image and the floating image is estimated by optimizing a similarity metric. Mutual information (MI), a popular similarity metric, is a reliable criterion for medical image registration. In this paper, we present an improved(More)
In this paper a novel approach is proposed for approximating Parks-McClellan low-pass differentiators using optimized low-order IIR filters. Indeed, a suitable IIR filter is designed for approximating Parks- McClellan Low pass differentiator using modified Al-Alaoui’s method, and then denominator polynomial coefficients of resulting transfer function(More)