(源码)基于深度学习的医学图像报告生成系统.zip

上传者: m0_62153576 | 上传时间: 2025-04-27 21:32:00 | 文件大小: 1.71MB | 文件类型: ZIP
# 基于深度学习的医学图像报告生成系统 ## 项目简介 本项目是一个基于深度学习的医学图像报告生成系统,旨在通过结合自然语言处理(NLP)和图像处理技术,自动生成针对医学X光图像的诊断报告。系统能够从输入的X光图像中提取关键信息,并生成详细的医学报告描述,帮助医生快速获取图像信息,提高诊断效率。 ## 项目的主要特性和功能 1. 图像特征提取使用预训练的CheXNet模型对X光图像进行特征提取,获取图像的高级表示。 2. 注意力机制在生成报告时,模型使用注意力机制关注图像中的关键区域,确保生成的报告内容准确且相关。 3. 文本处理采用LSTM(长短期记忆)网络处理文本数据,生成连贯且语义丰富的医学报告描述。 4. 多模态融合结合图像和文本信息,生成更加全面和准确的医学报告,确保信息的完整性和准确性。 5. 模型训练与评估提供完整的模型训练流程,包括数据加载、模型编译、训练、验证和评估,确保模型的性能和可靠性。

文件下载

资源详情

[{"title":"( 46 个子文件 1.71MB ) (源码)基于深度学习的医学图像报告生成系统.zip","children":[{"title":"model2.png <span style='color:#111;'> 48.74KB </span>","children":null,"spread":false},{"title":"predict.py <span style='color:#111;'> 1.98KB </span>","children":null,"spread":false},{"title":"final_local.py <span style='color:#111;'> 3.50KB </span>","children":null,"spread":false},{"title":"base_model.py <span style='color:#111;'> 20.21KB </span>","children":null,"spread":false},{"title":"create_model.py <span style='color:#111;'> 21.12KB </span>","children":null,"spread":false},{"title":"data_checkout.py <span style='color:#111;'> 1.36KB </span>","children":null,"spread":false},{"title":"README.assets","children":[{"title":"image-20210810201729285.png <span style='color:#111;'> 68.80KB </span>","children":null,"spread":false},{"title":"image-20210810165655043.png <span style='color:#111;'> 43.97KB </span>","children":null,"spread":false},{"title":"image-20210810160910694.png <span style='color:#111;'> 68.12KB </span>","children":null,"spread":false},{"title":"image-20210810212049367.png <span style='color:#111;'> 79.65KB </span>","children":null,"spread":false},{"title":"image-20210810201725782.png <span style='color:#111;'> 68.80KB </span>","children":null,"spread":false},{"title":"image-20210810120829065.png <span style='color:#111;'> 24.01KB </span>","children":null,"spread":false},{"title":"image-20210810214144275.png <span style='color:#111;'> 62.78KB </span>","children":null,"spread":false},{"title":"image-20210810135913712.png <span style='color:#111;'> 47.75KB </span>","children":null,"spread":false},{"title":"image-20210810195935826.png <span style='color:#111;'> 49.41KB </span>","children":null,"spread":false},{"title":"image-20210810123006178.png <span style='color:#111;'> 25.67KB </span>","children":null,"spread":false},{"title":"image-20210810213419828.png <span style='color:#111;'> 10.31KB </span>","children":null,"spread":false},{"title":"image-20210810140040483.png <span style='color:#111;'> 33.09KB </span>","children":null,"spread":false},{"title":"image-20210810213700700.png <span style='color:#111;'> 55.42KB </span>","children":null,"spread":false},{"title":"image-20210810195616660.png <span style='color:#111;'> 166.23KB </span>","children":null,"spread":false},{"title":"image-20210810195424976.png <span style='color:#111;'> 78.19KB </span>","children":null,"spread":false},{"title":"image-20210810193655765.png <span style='color:#111;'> 69.53KB </span>","children":null,"spread":false},{"title":"image-20210810140226604.png <span style='color:#111;'> 16.40KB </span>","children":null,"spread":false},{"title":"image-20210810194320318.png <span style='color:#111;'> 18.10KB </span>","children":null,"spread":false},{"title":"image-20210810193200375.png <span style='color:#111;'> 71.15KB </span>","children":null,"spread":false},{"title":"image-20210810212908406.png <span style='color:#111;'> 55.43KB </span>","children":null,"spread":false},{"title":"image-20210810135937973.png <span style='color:#111;'> 121.24KB </span>","children":null,"spread":false},{"title":"image-20210810135956793.png <span style='color:#111;'> 143.93KB </span>","children":null,"spread":false},{"title":"image-20210810135743559.png <span style='color:#111;'> 35.92KB </span>","children":null,"spread":false},{"title":"image-20210810161045830.png <span style='color:#111;'> 47.71KB </span>","children":null,"spread":false},{"title":"image-20210810133002501.png <span style='color:#111;'> 22.39KB </span>","children":null,"spread":false},{"title":"image-20210810165538392.png <span style='color:#111;'> 26.25KB </span>","children":null,"spread":false},{"title":"image-20210810171203993.png <span style='color:#111;'> 196.96KB </span>","children":null,"spread":false}],"spread":false},{"title":"requirements.txt <span style='color:#111;'> 165B </span>","children":null,"spread":false},{"title":"DataLoader.py <span style='color:#111;'> 7.78KB </span>","children":null,"spread":false},{"title":"train.py <span style='color:#111;'> 363B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"DataLoader.cpython-38.pyc <span style='color:#111;'> 5.37KB </span>","children":null,"spread":false},{"title":"DataLoader.cpython-36.pyc <span style='color:#111;'> 5.30KB </span>","children":null,"spread":false},{"title":"config.cpython-38.pyc <span style='color:#111;'> 806B </span>","children":null,"spread":false},{"title":"base_model.cpython-38.pyc <span style='color:#111;'> 12.17KB </span>","children":null,"spread":false},{"title":"config.cpython-36.pyc <span style='color:#111;'> 810B </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 2.19KB </span>","children":null,"spread":false},{"title":"Attention_Model.py <span style='color:#111;'> 13.15KB </span>","children":null,"spread":false},{"title":"data_process.py <span style='color:#111;'> 15.99KB </span>","children":null,"spread":false},{"title":"config.py <span style='color:#111;'> 2.36KB </span>","children":null,"spread":false},{"title":"final.py <span style='color:#111;'> 4.40KB </span>","children":null,"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明