血浆絮状物无损检测系统设计  

Design of nondestructive test system for plasma clots

作　　者：陈里里[1,2] 廖强[1,2] 杨正书[1] 胡雪[3] 张国珍[3] 

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400044 [2]重庆大学机械工程学院,重庆400044 [3]重庆医科大学附属第一医院输血科,重庆400016

出　　处：《重庆大学学报（自然科学版）》2012年第3期40-46,共7页Journal of Chongqing University

基　　金：重庆市自然科学基金资助项目(CSTC2006BB3176);重庆市科委攻关项目(CSTC2008AC3026);重庆大学'211工程'三期创新人才培养计划建设项目(S-09106);重庆市卫生局科研项目(2010-2-086)

摘　　要：检测血浆中是否含有絮状物是保证输血安全的重要措施。针对絮状物人工检测法的缺点,设计基于机器视觉技术和神经网络的血浆絮状物无损检测系统,并对系统设计的关键技术进行研究。基于MATLAB平台设计系统软件以实现图像采集,并采用剪切、反色、中值滤波、灰度切割对图像进行预处理;采用fisher判别方法,结合迭代阈值分割法和标注矩阵连通区域选择法,消除气泡干扰,提取絮状物。系统通过基于BP神经网络建立的识别模型,完成血浆絮状物的判别。临床对比实验结果表明,系统能有效地检测出血浆中是否含有絮状物,具有较好的检测重复性和准确性。每袋样品从图像采集、处理到最终给出检测结果的时间不超过1min。One of the most important measures that are used to guarantee blood transfusion safety is to detect clots in the plasma before transfusion.To overcome the disadvantages of manual detection method,this research designs a nondestructive testing（NDT） system for plasma clots inspection based on machine vision technique and artificial neural networks.The key technology for system design are studied and presented.Image acquisition is performed by custom-designed software based on MATLAB platform,and the methods of image cut,reverse color,median filter as well as gray cutting are adopted to preprocess image.The use of fisher discrimination method,combined with iterative threshold segmentation method and the selection of connected domain,can successfully eliminate the interference of air bubble and correctly extract the image of plasma clots.Plasma clots are discriminated by a recognition model based on artificial neural network BP algorithms.The results of clinical contrast experiment shows that the system can effectively detect whether plasma contains plasma clots and the new system shows a much higher degree of repeatability and stability.From the image acquisition and processing to the recognition of plasma clots,the detecting time of a sample is no more than 1 min.

关 键 词：机器视觉 神经网络 血浆絮状物 智能无损检测 fisher判别方法 

分 类 号：R318.6[医药卫生—生物医学工程] TP391.41[医药卫生—基础医学]