Detection of Microcalcifications in Mammograms
Editor(s): Jasjit Singh Suri; Rangaraj M. Rangayyan
Author(s): Begoña Acha, Carmen Serrano, Rangaraj Rangayyan, J.D. Desautels
Published: 2006
Abstract
In Western countries, women have a higher than 1-in-8 chance of developing breast cancer during their lives. Breast cancer represents the most frequently diagnosed cancer in women. The National Cancer Institute of U.S.A. estimates that, based on current rates, 13.2% of women born today will be diagnosed with breast cancer at some time in their lives. In order to reduce mortality, early detection of breast cancer is important, because therapeutic actions are more likely to be successful in the early stages of the disease. For women whose tumors were discovered early by mammography, the five-year survival rate was about 82% as opposed to 60% for the cases where the tumors were not found early. Mammography is currently the best radiological technique available for early detection of nonpalpable breast cancer. However, it is difficult for radiologists to provide both accurate and uniform evaluations for the large number of mammograms that they have to interpret in screening programs where most of the cases are normal; it has been observed that 10-30% of breast lesions are missed during routine screening. The situation is even more challenging since the early malignancies have small size and subtle contrast when compared with normal breast structures. Double reading (as carried out, for example, by two radiologists) helps to reduce the number of false negatives by 5-15%. Digital image-processing techniques represent useful tools for helping radiologists to improve their diagnosis with the aid of computer systems. In this sense, different CAD (computer-aided diagnosis) tools have been developed for improving image quality, identifying malignant signs, enhancing mammographic features, etc. On the average, the reader's sensitivity can be increased by 10% with the assistance of CAD systems. Some works have studied this potential of CAD to improve radiologists' performance in detecting clustered microcalcifications. There are a number of different classes of abnormality that may be observed in mammograms. One of the most significant types of mammographic abnormality is microcalcification. Microcalcifications are tiny granule like deposits of calcium. They are relatively bright (dense) in comparison with the surrounding normal tissue, and are up to about 1 mm in diameter, with an average diameter of 0.3 mm. Microcalcifications are of particular clinical significance when found in clusters of three or more within a square-centimeter region of a mammogram. Lanyi has described microcalcifications as “the most important leading symptom in mammographic detection of preclinical carcinomas.” Sickles noted that more than 50% of nonpalpable cancers had mammographically visible calcifications, and in 36% of nonpalpable cancers, calcifications were the only sign of abnormality. In an important study of cancers missed in screening mammography, it was observed that the presence of microcalcifications was the predominant feature in 18% of the missed cancers.
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Cited by 19 scholarly publications.
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KEYWORDS
Mammography

Cancer

Breast cancer

Computer aided diagnosis and therapy

Breast

Computing systems

Tumors

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