摘要
医学图像处理的智能化是医学图像领域应用的一个重要研究方向。传统的医学图像分析往往是开环的,图像的分割算法独立于后续图像的识别,智能化低,对检测员的技术水平要求较高。鉴于此,本文将强化学习运用于血细胞图像,采用闭环机制将血细胞的特征信息反馈到图像的分割算法中,并对分割效果进行评价,实现血细胞图像分割的智能化。
Intelligent medical image processing is an important research direction in the field of medical image applications.Traditional medical image analysis is often open-loop,and the image segmentation is independent of the image recognition with low intelligence,which requires inspectors with higher skill level.In consideration of these facts,reinforcement learning is applied to blood cell image,which use the blood cell features information as feedback for the image segmentation and evaluate the segmentation results in order to realize the closed-loop intelligent blood cell image segmentation.
出处
《计算机与现代化》
2013年第2期31-34,共4页
Computer and Modernization
关键词
医学图像分割
强化学习
血细胞特征
智能化
medical image segmentation
reinforcement learning
blood cell features
intelligent
