现代信息科技2026，Vol.10Issue(2)：79-83,5.DOI:10.19850/j.cnki.2096-4706.2026.02.015
基于ASP.NET与深度学习的医学图像分割系统设计与实现
Design and Implementation of Medical Image Segmentation System Based on ASP.NET and Deep Learning
陈少洁 1陈荣征1
作者信息
- 1. 广东职业技术学院,广东 佛山 528041
- 折叠
摘要
Abstract
To address engineering problems in the integration of Deep Learning models and traditional Web information systems,this paper designs and implements a loosely coupled and highly available medical image segmentation information management system.The system adopts B/S architecture.It develops the user interface and business logic based on the ASP.NET framework at the front-end,and calls the independently deployed Mask R-CNN model service through RESTful API at the back-end to complete image segmentation tasks.It adopts SQL Server database for data management and designs an asynchronous task processing mechanism.It successfully builds a management system integrating user management,patient information management,image upload,and asynchronous segmentation task scheduling.Tests verify the effectiveness of the system architecture in function,performance,and heterogeneous service communication.This study provides a feasible scheme for solving engineering integration problems of Deep Learning models in medical information systems.The proposed loosely coupled architecture has good practicality and scalability.关键词
信息管理系统/系统集成/ASP.NET/Mask R-CNN/B/S架构Key words
information management system/system integration/ASP.NET/Mask R-CNN/B/S architecture分类
信息技术与安全科学引用本文复制引用
陈少洁,陈荣征..基于ASP.NET与深度学习的医学图像分割系统设计与实现[J].现代信息科技,2026,10(2):79-83,5.
