National Institute for Astrophysics, Optics, and Electronics, Luis Enrique Erro No. 1, Puebla, 72840, Mexico.
Adv Exp Med Biol. 2011;696:451-9. doi: 10.1007/978-1-4419-7046-6_45.
Breast cancer is one of the main causes of death in women. However, its early detection through microcalcifications identification is a powerful tool to save many lives. In this study, we present a supervised microcalcifications detection method based on Fisher's Linear Discriminant. Our method considers knowledge about breast density allowing it to identify microcalcifications even in difficult cases (when there is not high contrast between the microcalcification and the surrounding breast tissue). We evaluated our method with two mammograms databases for each of its phases: breast density classification, microcalcifications segmentation, and false-positive reduction, obtaining cumulative accuracy results around 90% for the microcalcifications detection task.
乳腺癌是女性死亡的主要原因之一。然而，通过微钙化的识别进行早期检测是挽救许多生命的有力工具。在这项研究中，我们提出了一种基于 Fisher 线性判别法的监督微钙化检测方法。我们的方法考虑了关于乳房密度的知识，从而允许它即使在困难的情况下（微钙化与周围乳房组织之间没有高对比度时）也能识别微钙化。我们使用两个乳腺 X 线照片数据库来评估我们的方法，每个阶段都有：乳房密度分类、微钙化分割和假阳性减少，微钙化检测任务的累计准确率约为 90%。
