Robust automatic breast and pectoral muscle segmentation from scanned mammograms
نویسندگان
چکیده
Breast skin–air interface and pectoral muscle segmentation are usually first steps in all CAD applications on scanned as well as digital mammograms. Breast skin–air interface segmentation is much more difficult task when performed on scanned mammograms than on digital mammograms. In case of pectoral muscle segmentation, segmentation difficulty of analog and digital mammograms is usually similar. In this paper we present adaptive contrast enhancement method for breast skin–air interface detection which combines usage of adaptive histogram equalization method on small region of interest which contains actual edge and edge detection operators. Pectoral muscle detection method uses combination of contrast enhancement using adaptive histogram equalization and polynomial curvature estimation on selected region of interest. This method makes segmentation of very low contrast pectoral muscle areas possible because of estimation used to segment areas which have lower contrast difference than detection
منابع مشابه
A novel and automatic pectoral muscle identification algorithm for mediolateral oblique (MLO) view mammograms using ImageJ
Pectoral muscle identification is often required for breast cancer risk analysis, such as estimating breast density. Traditional methods are overwhelmingly based on manual visual assessment or straight line fitting for the pectoral muscle boundary, which are inefficient and inaccurate since pectoral muscle in mammograms can have curved boundaries. This paper proposes a novel and automatic pecto...
متن کاملAutomatic Mammogram image Breast Region Extraction and Removal of Pectoral Muscle
Currently Mammography is a most effective imaging modality used by radiologists for the screening of breast cancer. Finding an accurate, robust and efficient breast region segmentation technique still remains a challenging problem in digital mammography. Extraction of the breast profile region and the removal of pectoral muscle are essential pre-processing steps in Computer Aided Diagnosis (CAD...
متن کاملAutomatic Mammogram image Breast Region Extraction and Removal of Pectoral Muscle
Currently Mammography is a most effective imaging modality used by radiologists for the screening of breast cancer. Finding an accurate, robust and efficient breast region segmentation technique still remains a challenging problem in digital mammography. Extraction of the breast profile region and the removal of pectoral muscle are essential pre-processing steps in Computer Aided Diagnosis (CAD...
متن کاملRemoval of Pectoral Muscle Region in Digital Mammograms using Binary Thresholding
The pectoral muscle represents a predominant density region in Medio-Lateral Oblique (MLO) views of mammograms, which appears at approximately the same density as the dense tissues of interest in the image and can affect the results of image analysis methods. Therefore, segmentation of pectoral muscle is important in order to limit the search for the breast abnormalities only to the breast regi...
متن کاملAutomatic Detection of Pectoral Muscle Region for Computer-Aided Diagnosis Using MIAS Mammograms
The computer-aided detection (CAD) systems have been developed to help radiologists with the early detection of breast cancer. This system provides objective and accurate information to reduce the misdiagnosis of the disease. In mammography, the pectoral muscle region is used as an index to compare the symmetry between the left and right images in the mediolateral oblique (MLO) view. The pector...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Signal Processing
دوره 93 شماره
صفحات -
تاریخ انتشار 2013