Bao Kongjun, Bao Yaoxi
Engineering Training Centre, Zhengzhou University of Light Industry, Zhengzhou 450000, China.
Outpatient Department of Xicheng Branch, Luohe Central Hospital, Luohe 462400, China.
J Healthc Eng. 2021 Nov 22;2021:6549891. doi: 10.1155/2021/6549891. eCollection 2021.
In order to study the application of image processing technology in remote monitoring and intelligent medical systems, the principle and implementation method of a remote intelligent image monitoring system based on virtual local area network is proposed; this method analyzes the key technologies to be considered in the remote realization of image monitoring, adopts advanced digital image compression coding and decoding technology and digital image transmission technology, and applies intelligent image processing and recognition technology to display, adjust, and track images; it overcomes the defects that the general monitoring system requires excessive intervention by monitoring personnel and low intelligence. After verification, the experimental results show that the proposed model can accurately and efficiently segment nonoverlapping cervical cell images, and compared with other existing models, this model has both higher segmentation accuracy and faster calculation speed. The application of multicast is still only in the laboratory or small local area network; with the further development of network technology, its application prospects will be very broad.
为研究图像处理技术在远程监测和智能医疗系统中的应用，提出了一种基于虚拟局域网的远程智能图像监测系统的原理及实现方法；该方法分析了远程实现图像监测需考虑的关键技术，采用先进的数字图像压缩编码与解码技术以及数字图像传输技术，并应用智能图像处理与识别技术对图像进行显示、调整和跟踪；克服了一般监测系统需监测人员过多干预且智能化程度低的缺陷。经验证，实验结果表明所提模型能够准确、高效地分割非重叠宫颈细胞图像，与其他现有模型相比，该模型具有更高的分割精度和更快的计算速度。组播的应用目前仍仅在实验室或小型局域网中；随着网络技术的进一步发展，其应用前景将非常广阔。
