Ding Yong, Dai Hang, Zhang Hang
Institute of VLSI Design, Zhejiang University, Hangzhou 310027, China.
Biomed Mater Eng. 2014;24(6):3049-54. doi: 10.3233/BME-141126.
For improving the detection of micro-calcifications (MCs), this paper proposes an automatic detection of MC system making use of multi-fractal spectrum in digitized mammograms. The approach of automatic detection system is based on the principle that normal tissues possess certain fractal properties which change along with the presence of MCs. In this system, multi-fractal spectrum is applied to reveal such fractal properties. By quantifying the deviations of multi-fractal spectrums between normal tissues and MCs, the system can identify MCs altering the fractal properties and finally locate the position of MCs. The performance of the proposed system is compared with the leading automatic detection systems in a mammographic image database. Experimental results demonstrate that the proposed system is statistically superior to most of the compared systems and delivers a superior performance.
为了提高微钙化(MCs)的检测率,本文提出了一种利用数字化乳腺X线片中的多重分形谱自动检测MCs的系统。自动检测系统的方法基于这样一个原理:正常组织具有一定的分形特性,这些特性会随着MCs的出现而改变。在该系统中,多重分形谱被用于揭示这种分形特性。通过量化正常组织和MCs之间多重分形谱的偏差,该系统可以识别出改变分形特性的MCs,并最终定位MCs的位置。在所提出的系统与乳腺X线图像数据库中领先的自动检测系统进行了性能比较。实验结果表明,所提出的系统在统计学上优于大多数比较系统,并具有卓越的性能。