PURPOSE Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI) of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported. MATERIALS AND METHODS The study c...

<span>This paper presents a convolutional neural network (CNN) based non-invasive pathological voice detection algorithm using signal processing approach. The proposed extracts an acoustic feature, called chromagram, from samples and applies this feature to the input of CNN for classification. main advantage chromagram is that it can mimic way humans perceive pitch in sounds hence be cons...

The aim of this work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. With our research and based on a feature selection in different phases, we are trying to design a neural network system with an optimal neuron number in a hidden layer. Our approach consists of three steps: feature selectio...

objective: diabetes is one of the most common metabolic diseases. earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...

A computational technique is proposed for the segmentation, detection and analysis of pathological tissues, healthy tissues and Cerebrospinal fluid (CSF) of brain with the help of FLAIR brain magnetic resonance images. Composite feature vectors are extracted from the blocks of size 4 × 4 pixels of intra-cranial brain image. Then using fuzzy C mean algorithm, clustering of feature vectors and se...

This paper considers the computer–based support for the localization of pathological tissue within tomographic data. The subject of the approach is the inter–patient analysis of brain tissue types such as tumor, CSF, white matter, grey matter, bone, fat tissue and background. The class tumor hereby represents the superset of pathological tissue. The analysis pipeline of the presented approach c...

In this study a well-characterized pathological mutation at nucleotide position 3243 of human mitochondrial DNA was introduced into human rho(0) teratocarcinoma (NT2) cells. In cloned and mixed populations of NT2 cells heteroplasmic for the mutation, mitotic segregation toward increasing levels of mutant mitochondrial DNA always occurred. Rapid segregation was frequently followed by complete lo...