Mammography remains the most effective tool for the early detection of breast cancer and ComputerAided Diagnosis (CADx) is usually used as a second opinion by the radiologists. The main objective of our study is to introduce a method to generate and select the features of suspicious lesions in mammograms and classifying them by using support vector machine, in order to build a CADx system to di...

Distinguishing true retinal area from artefacts in SLO images is a challenging task, which is the first important step towards computeraided disease diagnosis. In this paper, we have developed a new method based on superpixel feature analysis and classification approaches for determination of retinal area scanned by Scanning Laser Ophthalmoscope(SLO). Our prototype has achieved the accuracy of ...

This paper presents a robust algorithm for the comparison of mammogram pairs. Salient regions are extracted in a topographic way. An integral invariant representation of shape, in combination with area and distance measures, are used for establishing their correspondences. The experimental results demonstrate that the algorithm can provide a useful tool for a ComputerAided Diagnosis system in m...

Marzieh Kohandani Tafreshi, Bertrand Napoléon, Anne-Isabelle Lemaistre, Marc Giovannini, Virendra Joshi, et al.. Smart Atlas for Supporting the Interpretation of needle-based Confocal Laser Endomicroscopy (nCLE) of Pancreatic Cysts: First Classification Results of a ComputerAided Diagnosis Software based on Image Recognition. Digestive Disease Week (DDW 2014), May 2014, Chicago, United States. ...

With an increasing awareness of the needs of the disabled comes a major surge in research into ways of helping them through technology. One speciic area is the use of computer-generated speech output to overcome the disability of being non-verbal. Many such`communicators' are presently available, but they are only able to converse at a relatively low rate. This paper describes a method of impro...

Texture analysis is quite important operation in medical image processing. Wavelet based texture analysis is developed which gives better way of extracting inherent object and properties in medical image. It gives a robust technique in disease diagnosis and future of biophysical disorder ness in a body. Image processing has an important influence on the medical decision making process and even ...

Breast cancer affects 1 in 8 women in the United States. Early detection and diagnosis is key to recovery. ComputerAided Detection (CAD) of breast cancer helps decrease morbidity and mortality rates. In this study we apply Template Matching as a method for breast cancer detection to a novel data set comprised of mammograms annotated according to ground truth. Performance is evaluated in terms o...

Skin texture analysis is one of then challenging issues in the field of medical diagnosis. Various types of skin diseases are affecting human life like skin dryness, fungus, and allergic symptoms. The objective of this paper is to analyze the skin disease using texture analysis of skin image and by comparing the test image to a defined images or reference images. The matching of test and refere...

BACKGROUND Tumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical images METHODS Image texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods. RESULTS Early evidence suggests that texture analysis has the p...