IEEE Trans Med Imaging. 2013 Dec;32(12):2169-78. doi: 10.1109/TMI.2013.2275151. Epub 2013 Jul 29.
The effectiveness of the treatment of breast cancer depends on its timely detection. An early step in the diagnosis is the cytological examination of breast material obtained directly from the tumor. This work reports on advances in computer-aided breast cancer diagnosis based on the analysis of cytological images of fine needle biopsies to characterize these biopsies as either benign or malignant. Instead of relying on the accurate segmentation of cell nuclei, the nuclei are estimated by circles using the circular Hough transform. The resulting circles are then filtered to keep only high-quality estimations for further analysis by a support vector machine which classifies detected circles as correct or incorrect on the basis of texture features and the percentage of nuclei pixels according to a nuclei mask obtained using Otsu's thresholding method. A set of 25 features of the nuclei is used in the classification of the biopsies by four different classifiers. The complete diagnostic procedure was tested on 737 microscopic images of fine needle biopsies obtained from patients and achieved 98.51% effectiveness. The results presented in this paper demonstrate that a computerized medical diagnosis system based on our method would be effective, providing valuable, accurate diagnostic information.
乳腺癌的治疗效果取决于其是否能及时被发现。诊断的早期步骤是对直接从肿瘤中获得的乳腺材料进行细胞学检查。这项工作基于对细针活检的细胞学图像进行分析，报告了计算机辅助乳腺癌诊断的进展，旨在对这些活检进行良性或恶性的特征描述。该研究不依赖于细胞核的精确分割，而是使用圆形霍夫变换估计细胞核的圆形。然后对得到的圆进行过滤，只保留高质量的估计值，以供支持向量机进行进一步分析，支持向量机根据纹理特征和根据 Otsu 阈值化方法获得的细胞核掩模的细胞核像素百分比，将检测到的圆分类为正确或错误。四个不同的分类器使用细胞核的 25 个特征来对活检进行分类。通过对从患者中获得的 737 张细针活检的显微镜图像进行了完整的诊断程序测试，实现了 98.51%的有效性。本文介绍的结果表明，基于我们的方法的计算机化医疗诊断系统将是有效的，可提供有价值的、准确的诊断信息。
