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Feature selection in computer aided diagnostic system for microcalcification detection in digital mammograms

In this paper an approach is proposed to develop a computer-aided diagnosis (CAD) system that can be very helpful for radiologist in diagnosing microcalcifications' patterns in digitized mammograms earlier and faster than typical screening programs and showed the efficiency of feature selection on the CAD system. The proposed method has been implemented in four stages: (a) the region of interest

Artificial Intelligence
Healthcare
Software and Communications

Modeling the interaction of brain regions based on functional magnetic resonance imaging time series

We propose a model that describes the interaction of several Brain Regions based on Functional Magnetic Resonance Imaging (FMRI) time series to make inferences about functional integration and segregation within the human brain. The method is demonstrated using dynamic causal modeling (OeM) using real data to show how such models are able to characterize interregional dependence. We extend

Artificial Intelligence
Healthcare

Computer aided diagnosis system for classification of microcalcifications in digital mammograms

Breast cancer is the main cause of death for women between the ages of 35 to 55. Mammogram breast X-ray is considered the most reliable method in early detection of breast cancer. Microcalcifications are among the earliest signs of a breast carcinoma. Actually, as radiologists point out, microcalcifications can be the only mammographic sign of non-palpable breast disease which are often overseen

Artificial Intelligence
Healthcare

Modeling of ultrasound hyperthermia treatment of breast tumors

Ultrasound hyperthermia has become one of the new therapeutic modalities for breast cancer treatment, since ultrasound appears to selectively affect malignant cells without causing any deleterious effects to the surrounding normal tissues. The main objective of this study is to numerically simulate the interaction of therapeutic ultrasound with a multi- tissue type system, and to develop an

Healthcare

Ultrafast localization of the optic disc using dimensionality reduction of the search space

Optic Disc (OD) localization is an important pre-processing step that significantly simplifies subsequent segmentation of the OD and other retinal structures. Current OD localization techniques suffer from impractically-high computation times (few minutes/image). In this work, we present an ultrafast technique that requiresless than a second to localize the OD. The technique is based on reducing

Artificial Intelligence

MLP, gaussian processes and negative correlation learning for time series prediction

Time series forecasting is a challenging problem, that has a wide variety of application domains such as in engineering, environment, finance and others. When confronted with a time series forecasting application, typically a number of different forecasting models are tested and the best one is considered. Alternatively, instead of choosing the single best method, a wiser action could be to choose

Artificial Intelligence

Ultrafast optic disc localization using projection of image features

Optic Disc (OD) localization is a fundamental step in developing computer-assisted diagnostics. In this work, an ultrafast method to locate the OD in retinal fundus images is presented. The proposed method is based on transforming the localization problem into two 1D problems by projecting the image features onto two perpendicular directions. Image features such as the directionality of the

Artificial Intelligence

A secure face verification system based on robust hashing and cryptography

Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which employs a user dependent one way transformation based on a two stage hashing algorithm.We first hash the face image using a two stages robust image hashing

Software and Communications

WinBioinfTools: Bioinformatics tools for windows cluster

Open source bioinformatics tools running under MS Windows are rare to find, and those running underWindows HPC cluster are almost nonexisting, in spite of the fact that Windows is the most popular operating system. Therefore, we introduce WinBioinfTools, an open source toolkit containing a number of bioinformatics tools running under Windows High Performance Computing Server 2008. The current

Artificial Intelligence

Preventing wormhole attack in wireless ad hoc networks using cost-based schemes

Ad hoc networks can be rapidly deployed and reconfigured. Hence, they are very appealing as they can be tailored to lots of applications. Due to their features, they are vulnerable to many attacks. A particularly severe security attack, called the wormhole attack, has been introduced in the context of ad-hoc networks. During the attack a malicious node captures packets from one location in the

Artificial Intelligence