癌症细胞扩展速度建模的仿真分析  

Modeling and Simulation of Cancer Cell Expansion Velocity

作　　者：森干[1] 

机构地区：[1]新疆医科大学医学工程学院,新疆乌鲁木齐830011

出　　处：《计算机仿真》2014年第8期259-262,272,共5页Computer Simulation

基　　金：癫痫EEG相空间变换;混沌特征指标和综合分析模型的研究(61263011);社区卫生服务管理系统的研究与构建(XJC201131)

摘　　要：癌症细胞具有易扩散转移的特点,对癌症患者的癌细胞的扩散速度进行检测,能够准确判断癌变程度并采取相应的治疗手段进行治疗。传统的癌症细胞扩展速度检测方法是基于癌变部位与周围正常肝脏组织图像的像素灰度比进行检测的。在癌症早期,由于癌细胞数量所占比例较低,癌变部位与周围的正常部位的像素灰度难以区别,导致比例不准,检测准确率降低。为提高准确性,提出一种像素密度的癌细胞扩展速度检测方法,利用被检测部位的癌细胞的像素密度,进行直方图转换,保证特征的可量化性,去除干扰噪声,保证特征对比的纯粹性。利用优化像素密度特征建立癌症细胞扩展模型,对癌细胞的扩展速度进行量化表示,从而判断出癌症细胞的扩展速度。实验结果表明,利用基于像素密度的癌细胞检测方法能够快速准确地对癌细胞扩展速度进行检测,衡量效果很好。Traditional detection method of cancer cell expansion velocity is based on the image pixel comparison of cancerous parts with normal liver tissue. At an early stage of cancer, due to the low proportion of cancer ceils, the image pixel of cancerous parts is indistinguishable from that of the surrounding normal parts, which results in lower detection accuracy. This paper presents a new detection method of cancer cell expansion velocity, which uses the pix- el density of the cancer cells in tested part to convert the histogram. It ensures that the characteristics of cancer cells can be quantified. The interference noise is removed, and the purity of feature correlation is guaranteed. A cancer cell extension model is established based on optimization of pixel density characteristics, which quantifies the exten- sion velocity of cancer cells, so as to judges the extension velocity of cancer cells. Experimental results show that the cancer cell detection method based on pixel density can fast detect the cancer cell extended velocity, the measure effect is quite good.

关 键 词：癌症细胞 像素灰度 像素密度 建模 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]