基于神经网络融合模型的头颅灌注图像分析

摘要

Objective To improve the diagnosis of cerebrovascular diseases by intelligent integration model. Methods With some head perfusion images, multiple integration analysis was performed for one-parameter images and raw grayscale images by neural network integration model. Results Stereoscopic and automatic analysis of multi-parameter cranial perfusion imaging was realized. Conclusion The analysis of conclusion Cranial perfusion imaging based on neural network integration model can be used for intelligent diagnosis of cerebrovascular diseases.%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.