首页|基于深度学习的"易诊"智能阅片系统的构建研究

基于深度学习的"易诊"智能阅片系统的构建研究

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为了实现肝包虫病病灶的提前识别和精确诊断,使用基于深度学习技术的智能阅片系统"易诊"开发微信小程序,以辅助新疆偏远地区的用户对肝包虫病超声图像进行肝包虫病病灶区域的识别。采用卷积神经网络(CNN)等深度学习技术,实现医学影像数据的自动分析和诊断。经过测试和评估,该系统表现优异,所开发的微信小程序实现了移动端医学影像上传和病灶区域的识别分析。通过深度学习算法进行图像诊断分析,并实时展示分析结果,该微信小程序提供方便易用的上传医学图像的功能,助力医疗条件薄弱地区提高肝包虫病的诊断效率和诊断精度。
Research on the Construction of an"Yizhen"Intelligent Film Reading System Based on Deep Learning
In order to achieve early recognition and accurate diagnosis of liver hydatid disease lesions,an intelligent film reading system based on Deep Learning technology called"Yizhen"is used to develop a WeChat Mini Program to assist users in remote areas of Xinjiang in identifying liver hydatid disease lesion areas in ultrasound images of liver hydatid disease.It uses Deep Learning technologies such as Convolutional Neural Networks(CNN)to achieve the automatic analysis and diagnosis of medical image data.After testing and evaluation,this system performed excellently,and the developed WeChat Mini Program achieved mobile end medical image uploading and lesion area recognition analysis.It uses Deep Learning algorithms for image diagnosis and analysis,and real-time displays of analysis results.This WeChat Mini Program provides a convenient and easy-to-use function for uploading medical images,helping to improve the diagnostic efficiency and accuracy of liver hydatid disease in areas with weak medical conditions.

WeChat Mini ProgramDeep Learningimage processingintelligent film reading

米吾尔依提·海拉提、热娜古丽·艾合麦提尼亚孜、王正业、叶尔夏提·多力孔、严传波

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新疆医科大学公共卫生学院,新疆乌鲁木齐 830011

新疆医科大学医学工程技术学院,新疆乌鲁木齐 830011

微信小程序 深度学习 图像处理 智能阅片

一流本科课程建设专项大学生创新创业训练计划国家自然科学基金&&

01030201011220211076000681560294CY2021010

2024

现代信息科技
广东省电子学会

现代信息科技

ISSN:2096-4706
年,卷(期):2024.8(9)
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