Nunes Fátima L S, Schiabel Homero, Goes Claudio E
Programa de Pós-Graduação em Ciência da Computação, Centro Universitário Eurípides de Marília, Av. Hygino Muzzi Filho, 529-Campus Universitário, 17525-901, Marília, SP, Brazil.
J Digit Imaging. 2007 Mar;20(1):53-66. doi: 10.1007/s10278-005-6976-5.
This paper presents a method to provide contrast enhancement in dense breast digitized images, which are difficult cases in testing of computer-aided diagnosis (CAD) schemes. Three techniques were developed, and data from each method were combined to provide a better result in relation to detection of clustered microcalcifications. Results obtained during the tests indicated that, by combining all the developed techniques, it is possible to improve the performance of a processing scheme designed to detect microcalcification clusters. It also allows operators to distinguish some of these structures in low-contrast images, which were not detected via conventional processing before the contrast enhancement. This investigation shows the possibility of improving CAD schemes for better detection of microcalcifications in dense breast images.
本文提出了一种在致密乳腺数字化图像中增强对比度的方法,这类图像是计算机辅助诊断(CAD)方案测试中的难题。开发了三种技术,并将每种方法的数据进行组合,以便在检测簇状微钙化方面取得更好的结果。测试期间获得的结果表明,通过组合所有开发的技术,可以提高旨在检测微钙化簇的处理方案的性能。它还使操作人员能够在低对比度图像中区分一些以前通过传统处理未检测到的这些结构。这项研究表明了改进CAD方案以更好地检测致密乳腺图像中微钙化的可能性。