Microcalcification is one of the key symptoms facilitating early detection of breast cancer. In this paper image are acquisition from the mini mias database and perform various steps they are image enhancement, feature extraction and classification .In image enhancement the images are enhanced using filters and the features are extracted from the enhanced image using Gabor filter, and classify ...

Computer-aided diagnosis techniques in medical imaging are developed for the automated differentiation between benign and malignant lesions and go beyond computer-aided detection by providing cancer likelihood for a detected lesion given image and/or patient characteristics. The goal of this study was the development and evaluation of a computer-aided detection and diagnosis algorithm for mammo...

PURPOSE Does the easier microcalcification detection (EMD) method enable sonographic visualization of microcalcifications in breast core biopsy specimens compared with mammography? MATERIALS AND METHODS In a prospective randomized study, 105 core biopsy specimens obtained with stereotactic guidance were examined by mammography and ultrasound. EMD is integrated in a high-end ultrasound system ...

Breast cancer continues to be a significant public health problem among women around the world. It has become the number one cause of cancer deaths amongst Malaysian women. The key to improve the breast cancer prognosis is by early detection. The important sign for the breast cancer detection is the presence of lesion such as microcalcification clusters (MCCs). In this review paper, the mammogr...

OBJECTIVE The objective of our study was to compare the detection and distinguishability of microcalcifications on mammograms obtained with a digital direct flat-panel detector versus an analog system using an anthropomorphic breast phantom. MATERIALS AND METHODS Studies were performed with a digital mammography system (Selenia) and an analog mammography system (Mammomat 3). Sixty-five transp...

Microcalcification clusters in mammograms are an important early sign of breast cancer. Varying densities of parenchymal tissue make visual detection of these masses very difficult. Computeraided diagnosis using wavelet transform is recently being used to improve the diagnostic accuracy and efficiency of screening mammography. Wavelet coeffcients describe the local geometry of an image in terms...

Detection of clustered microcalcifications (MCs) in mammograms represents a significant step towards successful detection of breast cancer since their existence is one of the early signs of cancer. In this paper, a new framework that integrates Bayesian classifier and a pattern synthesizing scheme for detecting microcalcification clusters is proposed. This proposed work extracts textural, spect...