This paper combines Struts and Hibernate two architectures together, using DAO (Data Access Object) to store and access data. Then a set of dual-mode humidity medical image library suitable for deep network is established, and a dual-mode medical image assisted diagnosis method based on the image is proposed. Through the test of various feature extraction methods, the optimal operating characteristic under curve product (AUROC) is 0.9985, the recall rate is 0.9814, and the accuracy is 0.9833. This method can be applied to clinical diagnosis, and it is a practical method. Any outpatient doctor can register quickly through the system, or log in to the platform to upload the image to obtain more accurate images. Through the system, each outpatient physician can quickly register or log in to the platform for image uploading, thus obtaining more accurate images. The segmentation of images can guide doctors in clinical departments. Then the image is analyzed to determine the location and nature of the tumor, so as to make targeted treatment.

翻译：本文融合Struts与Hibernate两种架构，采用数据访问对象（DAO）进行数据存储与访问。随后，建立了适用于深度网络的双模态湿度医学图像库，并提出基于该图像库的双模态医学图像辅助诊断方法。通过对多种特征提取方法的测试，曲线下最优操作特征积（AUROC）达到0.9985，召回率为0.9814，准确率为0.9833。该方法可应用于临床诊断，是一种实用方法。任何门诊医生均可通过系统快速注册，或登录平台上传图像以获取更准确的图像。通过该系统，每位门诊医生可快速注册或登录平台进行图像上传，从而获取更精准的图像。图像分割可指导临床科室医生进行诊断。随后，对图像进行分析以确定肿瘤的位置与性质，从而制定针对性治疗方案。