基于随机森林的肝脏CT图像病变识别方法

Xinyu Jin, Ting Zhang, Lanjuan Li, Haitao Wu, Bin Sun
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引用次数: 4

摘要

随机森林算法由于其在分类方面的优异表现,在机器学习领域得到了广泛的研究和发展。在肝脏CT图像识别方面,采用随机森林算法,利用图像灰度、纹理等特征向量,训练并发现几种常见肝脏病变的特征。提出了一种基于特征选择的改进随机森林算法。实验结果表明,改进后的算法获得了较好的分类精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lesion Recognition Method of Liver CT Images Based on Random Forest
Random forest algorithm has been intensively researched and developed in the field of machine learning, thanks to its considerable performance on classification. In terms of the identification of liver CT images, random forest algorithm is deployed to train and discover the characteristics of several common liver lesions through the usage of features vectors, such as image gray, texture, etc. This paper proposes an improved random forest algorithm based on feature selections. Concluding from experiment, the revised algorithm obtains a promising accuracy of classification.
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