基于智能化数据挖掘算法技术的辅助诊断系统设计研究

Research on Design of Auxiliary Diagnosis System Based on Intelligent Data Mining Algorithm Technology

数据挖掘技术能够从海量信息中提取出有价值的深层信息,再配合人工智能技术、大数据分析技术等辅助人类决策,在提高决策科学性、可靠性等方面有显著帮助。本文首先介绍了一种基于径向基函数的数据挖掘算法,随后概述了辅助诊断系统中重点应用的图像增强技术、特征提取技术。最后基于Windows系统和Delphi6.0开发语言,设计了乳腺癌辅助诊断系统。运行结果表明,该系统可对乳腺影像图片进行去噪和增强处理,勾画轮廓并提取形状特征,对病例进行良性/恶性诊断,利用生理切片数据做最后确诊,在辅助医师诊断决策方面应用效果良好。

Data mining technology can extract valuable deep information from massive information, and then cooperate with artificial intelligence technology and big data analysis technology to assist human decision-making, which is of great help in improving the scientificity and reliability of decision-making. This paper first introduces a data mining algorithm based on radial basis function, and then summarizes the image enhancement technology and feature extraction technology that are mainly used in the auxiliary diagnosis system. Finally, based on Windows system and Delphi6.0 development language, an auxiliary diagnosis system for breast cancer is designed. The operation results show that the system can denoise and enhance breast images, delineate contours and extract shape features, perform benign/malignant diagnosis of cases, and use physiological slice data for final diagnosis. It has a good application effect in assisting doctors in diagnosis and decision-making.