Cluster of microcalcification in mammograms are an important early sign of breast
cancer. This report presents a computer aided diagnosis (CAD) system for the automatic
detection of cluster rnicrocalcifications in digitized mammograms. The main objective of
this study is to present the approach for microcalcifications detection in mammography
image. In literature review author illustrate the techniques used in image processing,
segmentation, feature extraction and neural network in detecting rnicrocalcification. The
proposed system consists of two main steps. First step is image preprocessing and
segmentation in order to improve and enhance the quality of image. Then second step is
feature extraction to analyze the image and conclude whether the case is malignant or
benign. The programming of the project using MATLAB still need to be improved since
it produce the output that did not meet the author expectation especially in feature
extraction
