Automatic Breast Tissue Classification Based on BIRADS Categories
نویسندگان
چکیده
Introduction Breast cancer continues to be an important health problem. Early detection is needed to improve prognosis and significantly reduce women mortality. Computer-Aided Diagnosis systems (CAD) can help radiologist to improve their ability to detect and classify breast lesions. However, automated interpretation of mammogram lesions still remains very difficult. Some of the reasons are the dense tissues. They may cause suspicious areas to be almost invisible and may be easily misinterpreted as calcifications or masses. When processing a mammographic image with dense tissue using CAD systems it is sometimes necessary to adjust the input parameters to control the sensitivity of the algorithms in areas of high intensity and thus reduce false positive detections. Thus, it is possible to design optimal algorithms for a CAD system by previously using breast tissue classification.
منابع مشابه
A Comparison of Breast Tissue Classification Techniques
It is widely accepted in the medical community that breast tissue density is an important risk factor for the development of breast cancer. Thus, the development of reliable automatic methods for classification of breast tissue is justified and necessary. Although different approaches in this area have been proposed in recent years, only a few are based on the BIRADS classification standard. In...
متن کاملAutomatic Segmentation of the Dense Tissue in Digital Mammograms for BIRADS Density Categorization
Currently, the Breast Imaging Reporting and Data System (BIRADS) density categorization is the most popular tool for density assessment among radiologists. However, it is subject to interobserver variabilities. Therefore, different automated methods have been proposed for dense tissue segmentation. In [1], a technique based on modeling of breast tissue using a Gaussian mixture model was propose...
متن کاملLocal Feature Based Breast Tissue Appearance Modelling for Mammographic Risk Assessment
Many studies have indicated that there is a strong correlation between breast tissue density/patterns and the risk of developing breast cancer. Therefore, modelling breast tissue appearance in mammograms is important for automated mammographic risk assessment. In this paper, we present a method for building models of breast tissue appearance based on local features in mammographic images. Mammo...
متن کاملMammographic breast density in infertile and parous women.
BACKGROUND Mammographic breast density is a useful marker for breast cancer risk, as breast density is considered one of the strongest breast cancer risk factors. The study objective was to evaluate and compare mammographic breast density in infertile and parous women, as infertility may be associated with high breast density and cancer occurrence. METHODS This study evaluated mammographic br...
متن کاملStandards of the Polish Ultrasound Society – update. Sonomammography examination
The use of BIRADS classification has been recommended in sonomammography examinations in Poland since the year 2010. It was developed by the Polish Ultrasound Society and published in Ultrasound Examinations Standards of the Polish Ultrasound Society. Standards, based on BIRADS-usg classification, introduced uniformity in breast ultrasound examination descriptions and in the terminology of path...
متن کاملModelling Breast Tissue in Mammograms for Mammographic Risk Assessment
We propose to model breast tissue in mammograms covering both density and tissue patterns. The breast tissue density modelling is based on the global density distribution of the breast region. We segment the whole breast region into a number of uniform density sub-regions and construct an overall density model of the breast using the relative proportions of these sub-regions. The breast tissue ...
متن کامل