Presentation of images of lesions similar to that of an unknown lesion might be useful to radiologists in distinguishing between benign and malignant clustered microcalcifications on mammograms. Investigators have been developing computerized schemes to select similar images from large databases. However, whether selected images are really similar in appearance is not examined for most of the s...

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for ...

The aim of our research is to classify digital mammograms into two classes, abnormal microcalcification and normal. Texture is one of the major mammographic characteristics. The statistical textural of Gray Level Coocurrence Matrix (GLCM) used in characterizing images are contrast, energy and entropy. K-Nearest Neighbor (K-NN) and Fuzzy K-Nearest Neighbor (FK-NN) was proposed for classifying im...

The proposed method focuses on the prediction of breast cancer in its early stage. It is very difficult to detect microcalcification due to its small size and low contrast with respect to the surrounding tissues. A new, fast and simple enhancement technique is considered for early detection of breast cancer by enhancing microcalcification features using morphology and LOG filter. Target to back...

A novel approach to image enhancement of digital mammography images is introduced, for more accurate detection of microcalcification clusters. In original mammographic images obtained by X-ray radiography, most of the information is hidden to the human observer. The method is based on redundant discrete wavelet transform due to its good properties: shift invariance and numeric robustness. The p...

This paper presents an approach for detecting microcalcifications in digital mammograms. The microcalcifications appear i n small clusters of few pixels with relatively high intensity compared with their neighboring pixels. The processing scheme used here focuses on detection of microcalcification in a very weak contrast to their background and presents a computerized technique to identify the ...

AIMS To evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (MRI) in the diagnosis of BI-RADS-5 type of microcalcifications of the breast, to compare the size of the microcalcification lesions using mammography (MG) and MRI, and to determine the value of MRI in surgery for microcalcifications. The study also determines the morphology of microcalcification lesions, assesses...