Automatic segmentation and detection of brain tumor is a notoriously complicated issue in Magnetic Resonance Image. The similar state-of-art segmentation methods and techniques are limited for the detection of tumor in multimodal brain MRI. Thus this work deals about the accurate segmentation and detection of tumor in multimodal brain MRI and this research work is focused to improve automatic s...

Fuzzy logic and genetic algorithms are well-established computational techniques that have been employed to deal with the problem of classification as this is presented in the context of data mining. Based on Fuzzy Miner which is a recently proposed state-of-the-art fuzzy rule based system for numerical data, in this paper we propose GF-Miner which is a genetic fuzzy classifier that improves Fu...

This manuscript presents an automated classification approach to classify lesions into four categories of liver diseases, based on Computer Tomography (CT) images. The four diseases types are Cyst, Hemangioma, Hepatocellular carcinoma (HCC), and Metastasis. The novelty of the proposed approach is attributed to utilizing the difference of features (DOF) between the lesion area and the surroundin...

The Recent modern techniques, communication between humans and computers is proven a tremendous achievement in the field medical science. Computer hardware and signal processing have made possible the use of EEG signals or “brain waves” for Human-computer communication. Electroencephalography (EEG) is the electrical activity recording along the scalp. EEG refers to the recording of the spontane...

Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. Currently, there is a great interest in the development of Computer-Aided Diagnosis (CAD) systems for dermoscopic images. The segmentation step is one of the most important ones, since its accuracy determines the eventual success or failure of a CAD system. This study introduced new me...

It is important problems to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Although preventative techniques such as access control and authentication attempt to prevent intruders, these can fail, and as a second line of defence, intrusion detection has been introduced. Rare events are events that occur very infrequently, detection of rare event...

This paper introduces an automated medical data classification method using wavelet transformation (WT) and interval type-2 fuzzy logic system (IT2FLS). Wavelet coefficients, which serve as inputs to the IT2FLS, are a compact form of original data but they exhibits highly discriminative features. The integration between WT and IT2FLS aims to cope with both high-dimensional data challenge and un...

Brain ArterioVenous Malformation (BAVM) is an abnormal tangle of brain blood vessels where arteries shunt directly into veins with no intervening capillary bed which causes high pressure and hemorrhage risk. The success of treatment by embolization in interventional neuroradiology is highly dependent on the accuracy of the vessels visualization. In this paper the performance of clustering techn...

Usually, related works on color image segmentation train neural networks with the colors of the image to segment, then the number of dominant colors within the image is obtained in order to process the image using fuzzy cmeans, where the colors are represented in the RGB space. The drawback with these methods is the neural networks must be trained every time a new image is given; but also, in t...

This Brain tumors are the mechanisms to control normal cells randomly and uncontrolled multiplication of cells in which growth is an abnormal mass of tissue. A tumor growth takes place within the skull and interferes with normal brain activity. Therefore, the first step is very important in tumor detection. Various techniques have been developed to detect tumors in the brain. Most crucial task ...