This paper describes a method to detect microcalcifications in digital mammographic images using Two-dimensional Discrete Wavelet Transform and image enhancement techniques for removing noise as well as to obtain a better contrast. Calcifications are tiny deposits of calcium in breast tissues and they often represent important and common findings in a mammogram. The first step is to apply a segmentation process for eliminating some regions in the image, which are not useful for the mammographic interpretation. After, unsharp masking filter is used to improve the contrast of the image and to clarify some details like microcalcifications. Likewise, a histogram modification technique is employed to achieve better visualization of the microcalcifications and finally DWT (Discrete Wavelet Transform) must be applied for detecting the abnormality. Results were evaluated using the Mammographic Image Analysis Society (MIAS) Mammographic databases.