A system that automatically detects textural abnormalities in medical images will usually require three steps: 1) segmentation, that allows the selection of corresponding regions of interest; 2) texture feature extraction for each region of interest; 3) classification of regions, using the texture features and the ground truth from a training database. After classifying regions in the image, an...

The current study investigates whether texture properties of the tissue surrounding microcalcification (MC) clusters can contribute to breast cancer diagnosis. The case sample analyzed consists of 100 mammographic images, originating from the Digital Database for Screening Mammography (DDSM). All mammograms selected correspond to heterogeneously and extremely dense breast parenchyma and contain...

INTRODUCTION Visual inspection by magnetic resonance (MR) images cannot detect microscopic tissue changes occurring in MS in normal appearing white matter (NAWM) and may be perceived by the human eye as having the same texture as normal white matter (NWM). The aim of the study was to evaluate computer aided diagnosis (CAD) system using texture analysis (TA) in MR images to improve accuracy in i...

In this paper we present novel approaches for the computer aided diagnosis of leukoplakia on the vocal folds based on video endoscopic images of the larynx. The approaches applied for the classification of the vocal fold surface tissue are texture analysis methods, which have been enhanced to use spatial information as well as color information in one combined color texture approach. The multis...

skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. if they detected at an early stage, treatment can become simple and economically. accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. the aim of this study is to provide an effective approach to detect the skin lesion border on a purposed imag...

Computer methodologies are being developed to assist radiologists, as second readers, in the interpretation of mammograms. This could represent further amelioration by increasing diagnostic accuracy in the screening programs. We have developed a computerized scheme to detect clustered microcalcifications in digital mammograms, using 100 mammograms that were randomly selected from the mammograph...

Accuracy and efficiency are two major issues in designing CAD (Computer Aided Diagnosis) systems. Most of CAD systems are dedicated to visual feature extraction because it has been shown that visual information extracted from images can achieve similarity retrievals with high performance of effectiveness of the diagnosis, at the same time reducing the pain of the patients also. In the brain MR ...

Computer aided celiac disease diagnosis is based on endoscopic images showing the villi structure in regions of the small bowel. Especially unavoidably variable illuminations and varying viewing angles of the individual villi are a source for high intra-class as well as intraimage variations in the image domain. We clarify that common texture descriptors are unable to compensate such a high deg...