Mammograms are one of the most widely used techniques for preliminary screening of breast cancers. There is great demand for early detection and diagnosis of breast cancer using mammograms. Texture based feature extraction techniques are widely used for mammographic image analysis. In specific, wavelets are a popular choice for texture analysis of these images. Though discrete wavelets have bee...

OBJECTIVE AND METHODS To investigate the utility of nuclear chromatin texture assessment in the differential diagnosis of follicular patterned lesions, by means of examining 76 samples previously submitted to the immunohistochemical protein analysis of HBME-1, CK-19 and galectina-3. RESULTS HBME-1 confirmed to be the most sensitive marker of malignancy. A series of morphometric, densitometric...

In recent years, more foreign publications are devoted to the use of texture analysis or radiomics in solving certain diagnostic problems, including diagnosis hepatocellular cancer (HCC). This method processing medical images allows for a comprehensive assessment structure neoplasms by extracting large number quantitative features from images. The purpose study was determine role CT and MR diff...

Breast cancer is one of the most important causes of death among women in world between the age of 40 and 55. Breast cancer can be treated effectively only if it is detected at a premature stage. Imaging techniques play a considerable role in assisting breast biopsies, especially of abnormal areas that cannot be felt but can be seen on a conventional mammogram or other techniques. To help radio...

Noise is one of the major problems that hinder an effective texture analysis of disease in medical images, which may cause variability in the reported diagnosis. In this paper seven texture measurement methods (two wavelet, two model and three statistical based) were applied to investigate their susceptibility to subtle noise caused by acquisition and reconstruction deficiencies in computed tom...

Image segmentation plays a major role in the analysis of medical image disease diagnosis. Image features extracted is the basis for precise image segmentation. Variable nature of image features, such as size, shape, intensity, color, texture etc., cause complexity in the image segmentation and analysis of the image nature. Existing work estimate the effectiveness of the level-set shape beside w...