摘要
目的:针对脑血管疾病的常见诊断手段中存在一定程度的不足和局限,探讨用智能化混合融合模型进行诊断。方法:综合多例头颅灌注图像,利用神经网络融合模型的原理方法,对单参数图像和原始灰阶图像进行多重融合分析。结果:实现头颅灌注成像多参数图像综合分析立体化和自动化。结论:基于神经网络融合模型的头颅灌注图像分析方法,可以有效实现脑血管疾病诊断的智能化。
Objective To improve the diagnosis of cerebrovascular diseases by intelligent integration model. Mothods With some head perfusion images, multiple integration analysis was performed for one-parameter images and raw grayscale im- ages by neural network integration model. Rotndts Stereoscopic and automatic analysis of multi-parameter cranial perfusion imaging was realized. Conelution The analysis of conclusion Cranial perfusion imaging based on neural network integration model can be used for intelligent diagnosis of cerebrovascular diseases.[Chinese Medical Equipment Journal,2013,34 （1）： 19-21,31]
出处
《医疗卫生装备》
CAS
2013年第1期19-21,31,共4页
Chinese Medical Equipment Journal
关键词
灌注成像
机器学习
融合模型
神经网络
perfusion imaging
machine learning
integration model
neural network
