摘要
本研究利用影像学机器视觉技术实现对乳腺肿瘤病理图像识别方法的优化设计。首先,从影像学的角度分析乳腺肿瘤的病理特征,并以此作为病理图像识别的参考标准。安装机器视觉的硬件设备,通过机器视觉采集乳腺肿瘤病理初始图像,保证初始图像的清晰度。通过图像预处理、分割等步骤,提取病理图像中的特征。与影像学分析结果比对,得出乳腺肿瘤病理图像的识别结果。通过与传统图像识别方法的对比实验发现,影像学机器视觉技术使乳腺肿瘤病理图像识别优化方法的错误率降低了2.6%。
Due to the We adopted imaging machine vision technology to optimize the design of breast tumor pathological image recognition method.First of all,the pathological features of breast tumor were analyzed from the perspective of images,then as the reference standard for pathological image recognition.The hardware equipment of machine vision was installed,and the initial images of breast tumor pathology were collected by the machine vision to ensure the clarity of the initial images.Through images preprocessing,segmentation and other steps,the features of collected pathological images were extracted.Compared with the imaging analysis results,the recognition results of breast tumor pathological images were obtained.Compared with the traditional image recognition method,the error rate of the optimized method is reduced by 2.6%.
作者
陈佳
李高军
CHEN Jia;LI Gaojun(School of Medicine,Ankang University,Ankang 725000,China)
出处
《生物医学工程研究》
2020年第3期266-270,276,共6页
Journal Of Biomedical Engineering Research
基金
陕西省教育厅科研计划项目(18JK0008)。
关键词
影像学
机器视觉
乳腺肿瘤
病理图像
图像识别
Imaging
Machine vision
Mammary cancer
Pathological image
Image recognition
