利用图像分析技术进行癌细胞检测和病理定量分析。
Cancer cells detection and pathology quantification utilizing image analysis techniques.
作者信息
Goudas Theodosios, Maglogiannis Ilias
机构信息
University of Central Greece, Department of Computer Science and Biomedical Informatics, Greece.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4418-21. doi: 10.1109/EMBC.2012.6346946.
This paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images utilizing adaptive thresholding and a Support Vector Machines classifier. The segmentation results are also enhanced through a Majority Voting and a Watershed technique. The proposed tool was evaluated by experts on breast cancer images and the reported results were accurate and reproducible.
本文提出了一种先进的图像分析工具，用于利用自适应阈值处理和支持向量机分类器对显微镜图像中的癌细胞和凋亡细胞进行准确快速的表征和量化。分割结果还通过多数投票和分水岭技术得到增强。专家们对乳腺癌图像对所提出的工具进行了评估，报告的结果准确且可重复。
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