基于深度学习的医学图像诊断系统-计算机毕业设计源码+LW文档

摘 要
深度学习作为一种强大的机器学习方法，能够自动从大量数据中提取特征并进行模式识别，因此在医学图像诊断领域具有广阔的应用前景。本文旨在研究并开发一种基于深度学习的医学图像诊断系统，以提高医学图像诊断的准确性和效率。
本文首先介绍了医学图像诊断的重要性和挑战，以及深度学习在医学图像处理中的优势。接着，详细阐述了系统的主要技术，基于深度学习的医学图像诊断系统使用Python技术，MySQL数据库开发。然后分析设计了整体架构和思路。该系统主要由图像预处理、特征提取、分类器训练和诊断结果输出等模块组成。在特征提取阶段，我们利用深度学习模型自动学习图像中的有用信息，并将其转化为可用于分类的特征向量。通过训练分类器，系统能够学习从特征向量到诊断结果的映射关系。结果表明，该系统在多种医学图像诊断任务中均取得了较高的准确性和稳定性。与传统的诊断方法相比，基于深度学习的医学图像诊断系统不仅能够提高诊断的准确性，还能够减少医生的工作负担，提高诊断效率。

[关键词] 深度学习，python，医学图像，MySQL，图像诊断

 
Abstract
With the continuous progress of computer technology, significant progress has been made in various fields of society, and informatization has become an indispensable part of modern life. However, the traditional rental management model is no longer able to meet the modern people\\\'s pursuit of quality of life, and its service quality and speed are both insufficient. Many landlords, due to resource constraints such as human, material, and financial resources, find it difficult to fully showcase the characteristics and advantages of their properties on various websites, resulting in the loss of a large number of potential customers. The introduction of the management system for housing rental management not only significantly reduces the operating costs, but also simplifies the promotion process by taking advantage of the huge traffic advantage of the Internet. Therefore, designing an efficient housing rental management system is particularly important. This system can not only display housing information more intuitively, but also better adapt to the needs of the times.
This article first explores the background and significance of developing a housing rental system based on Spring Boot. Subsequently, through in-depth functional and non functional analysis, the specific requirements of the system were clarified. In the system design phase, we focused on detailed modeling from two aspects: functional design and database design. In terms of technical implementation, we have chosen Java as the backend development language, Vue technology for the client, and MySQL for the database. After coding and detailed planning of the implementation process, we have finally completed the construction of the entire system. To ensure the stability and functional integrity of the system, we conducted rigorous software testing. The test results show that the housing rental system based on Spring Boot fully meets the basic business needs of housing rental, can provide users with convenient online reservation services, and also provides efficient management tools for housing rental administrators.

[keywords] House rental; Landlord; Housing rental; Java;

 
目  录
摘 要 I
Abstract II
1 绪论 3
1.1 课题背景 3
1.2 课题意义 3
1.3 国内外研究现状 4
1.4 研究内容 5
2 相关技术介绍 7
2.1 系统开发环境 7
2.2 深度学习概述 7
2.3 Python技术 8
2.4 MySQL数据库 9
2.5 卷积神经网络算法 9
3 系统需求分析 11
3.1 可行性分析 11
3.1.1操作可行性 11
3.1.2经济可行性 11
3.1.3技术可行性 11
3.2 功能需求分析 11
3.3 非功能需求分析 13
4 系统设计 14
4.1 系统功能设计 14
4.2卷积神经网络算法设计 15
4.2.1数据处理与预处理 15
4.2.2模型构建与训练 16
4.3 数据库设计 18
5 系统实现 20
5.1会员注册登录的实现 20
5.2医学图像诊断的实现 20
5.2.1上传医学图像 20
5.2.2医学图像诊断 21
5.3后台管理 22
5.3.1用户管理 22
5.3.2诊断记录 23
6 系统测试 25
6.1测试目的 25
6.2功能测试 25
6.3测试总结 26
结    论 27
参 考 文 献 28
致 谢 29
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