空间二阶导数图像处理：在光学乳腺成像中用于增强乳腺肿瘤检测的应用。

Spatial second-derivative image processing: an application to optical mammography to enhance the detection of breast tumors.

作者信息

Pera Vivian E, Heffer Erica L, Siebold Horst, Schutz Oliver, Heywang-Kobrunner Sylvia, Gotz Linda, Heinig Anke, Fantini Sergio

机构信息

Tufts University, Bioengineering Center, Department of Biomedical Engineering, 4 Colby Street, Medford, Massachusetts 02155, USA.

出版信息

J Biomed Opt. 2003 Jul;8(3):517-24. doi: 10.1117/1.1578496.

DOI:10.1117/1.1578496

PMID:12880359

Abstract

We present an image-processing method that enhances the detection of regions of higher absorbance in optical mammograms. At the heart of this method lies a second-derivative operator that is commonly employed in edge-detection algorithms. The resulting images possess a high contrast, an automatic display scale, and a greater sensitivity to smaller departures from the local background absorbance. Moreover, the images are free of artifacts near the breast edge. This second-derivative method enhances the display of structural information in optical mammograms and may be used to robustly select areas of interest to be further analyzed spectrally to determine the oxygenation level of breast lesions.

摘要

我们提出了一种图像处理方法，该方法可增强对光学乳腺造影片中高吸收区域的检测。这种方法的核心是一种常用于边缘检测算法的二阶导数算子。生成的图像具有高对比度、自动显示比例，并且对与局部背景吸收率的较小偏差具有更高的灵敏度。此外，图像在乳腺边缘附近没有伪影。这种二阶导数方法增强了光学乳腺造影片中结构信息的显示，可用于稳健地选择感兴趣区域，以便进一步进行光谱分析，以确定乳腺病变的氧合水平。