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In this article, a novel model of computer aided diagnosis (CAD) system through breast thermography is proposed with the purpose of diagnosing breast cancer. There are two main factors that were considered in our system: the data base for the design and the type of inputs used for the classifiers. The suggested model is based on a fuzzy classifier using statistical features. The results of the CAD...
Breast cancer is a leading cause of cancer-related deaths in women worldwide. Discovery of breast cancer-related disease genes is becoming very important to researcher and opens a new way to investigate pathogenic mechanism of breast cancer. Many studies have shown that the availability of human genome-wide protein-protein interactions (PPI) provides us with new opportunity for discovering disease-genes...
Breast cancer is the most common cancer in many countries all over the world. Early detection of cancer, in either diagnosis or screening programs, decreases the mortality rates. Computer Aided Detection (CAD) is software that aids radiologists in detecting abnormalities in medical images. In this article we present our approach in detecting abnormalities in mammograms using digital mammography. Each...
The performance of mass segmentation is greatly influenced by an initial position of a mass. Some researchers performed mass segmentation with the initial position of a mass given by radiologists. The purpose of our research is to find the initial position for mass segmentation and to notify the segmented mass to radiologists without any additional information on mammograms. The proposed system consists...
Computer-aided detection (CAD) is used in medical science as a means of supporting a doctor's observations and interpretations. While X-ray imaging techniques, such as mammography, yield a great deal of information, it is not always easy to evaluate detected mammographic regions as being suspicious for cancer, which results in a number of cancers to be misinterpreted or missed in an image. In this...
A new hybrid approach for mammography segmentation is suggested in this work. The segmentations proceed by refining successively, in a way that macro regions at each step are recovered. Two segmentation techniques, thresholding and Markov field, enter in competition to segment theses regions. The technique which gives the best results according to a given criterion will take on the process. However,...
A semantic-based CAD system for mammography is proposed. Semantic layer is added to the computer aided diagnosis procedure by comprehend the lesion symptom of mammogram and clinical information. This provides doctor a complete and standardization semantic interpretation of the case. Final result is obtained through the synthetic analysis of the acquired semantic information by a Bayesian semantic...
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