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Digitized images have replaced analog images as photographs or x-rays in many different fields. In their raw form, digital images require a tremendous memory capacity for storage and large amount of bandwidth for transmission. In the last two decades, many researchers have been devoted to develop new techniques for image compression. More recently, wavelets(More)
Stroke is the third major cause of death worldwide behind heart disease and cancer. Carotid atherosclerosis is the most frequent cause of ischemic stroke. Early diagnosis of carotid plaque and serial monitoring of its size with the help of imaging modalities can help to prevent the atherosclerotic complications. The main difficulty is inevitable variability(More)
This paper presents a method for classification of liver ultrasound images based on texture analysis. The proposed method uses a set of seven texture features having high discriminative power which can be used by radiologists to classify the liver. Feature extraction is carried out using the following texture Based upon the results of Linear Discriminative(More)
Most existing wavelet-based image denoising techniques are developed for additive white Gaussian noise. In applications to speckle reduction in medical ultrasound (US) images, the traditional approach is first to perform the logarithmic transform (homomorphic processing) to convert the multiplicative speckle noise model to an additive one, and then the(More)
Background. Fine needle aspiration cytology is considered the gold standard diagnostic test for the diagnosis of thyroid nodules. Fine needle aspiration cytology is a cost effective procedure that provides specific diagnosis rapidly with minimal complications. Based on the cytology findings, patients can be followed in cases of benign diagnosis and(More)
In this paper, we propose to design a cross-layer based intrusion detection technique for wireless networks. In this technique a combined weight value is computed from the Received Signal Strength (RSS) and Time Taken for RTS-CTS handshake between sender and receiver (TT). Since it is not possible for an attacker to assume the RSS exactly for a sender by a(More)
Aim of this paper is to develop an efficient fuzzy c-mean based segmentation algorithm to extract tumor region from MR brain images. First, cluster centroids are initialized through data analysis of tumor region, which optimizes the standard fuzzy c-mean algorithm. Next, reconstruction based morphological operations are applied to enhance its performance(More)