mall项目是一套电商系统，包括前台商城系统及后台管理系统，基于SpringBoot+MyBatis实现，采用Docker容器化部署。 前台商城系统包含首页门户、商品推荐、商品搜索、商品展示、购物车、订单流程、会员中心、客户服务、帮助中心等模块。 后台管理系统包含商品管理、订单管理、会员管理、促销管理、运营管理、内容管理、统计报表、财务管理、权限管理、设置等模块。

Machine Learning for Tissue Deformation Modelling (MALTIDEM): Predicting tissue deformation in real time by expressing results from FEM simulations with machine learning

Implementation of PhysGNN (Accepted at NeurIPS2022)

This is a repository that contains codes to generate DRR from a CT scan

DRR generation by pycuda

"Neural Attenuation Fields for Sparse-View CBCT Reconstruction" (MICCAI 2022 Oral)

Image-to-Image Translation in PyTorch

[CVPR 2024] SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design

Code for "DeepDRR: A Catalyst for Machine Learning in Fluoroscopy-guided Procedures". https://arxiv.org/abs/1803.08606

✨基于卷积神经网络(CNN)和CIFAR10数据集的图像智能分类 Web 应用 Intelligent Image Classification Web Applcation based on Convolutional Neural Networks and the CIFAR10 Dataset✨🚩 (with README in English) 📌含在线demo：图像分类可视化界面，…

✨基于 3D 卷积神经网络(CNN)的阿尔兹海默智能诊断 Web 应用 Alzheimer's Intelligent Diagnosis Web Application based on 3D Convolutional Neural Network and the ADNI Dataset ✨ 🚩(with README in English) 📌含在线demo：医学影像识别系统，图像识…

基于深度学习的肿瘤分割系统的设计与实现

基于深度学习的肿瘤辅助诊断系统，以图像分割为核心，利用人工智能完成肿瘤区域的识别勾画并提供肿瘤区域的特征来辅助医生进行诊断。有完整的模型构建、后端架设、工业级部署和前端访问功能。TensorRT、PyTorch 、OpenCV 、Flask、Vue

设计并实现了一个基于深度学习、集成学习、迁移学习、GAN等技术的色素性皮肤病自动识别七分类系统。本系统主要由服务端和客户端两个模块组成。服务端基于深度学习、集成学习、迁移学习、GAN等技术实现了对色素性皮肤病自动识别七分类。客户端使用微信小程序和网站(SSM、Springboot)开发。用户通过微信小程序或网站上传图像到服务端，服务端返回所属类别。

毕业设计项目-基于深度学习的阿兹海默症早期诊断辅助系统设计与实现

毕业设计基于Opencv的车牌识别系统

MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

Unsupervised Learning for Image Registration

Official repository for LiftReg: Limited Angle 2D/3D Deformable Registration.

Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction: Implementation & Demo

A deep-learning approach for direct whole-heart mesh reconstruction

4D reconstruction of the lung surface using temporal sequences of MRI images

This is a 3D Slicer extension for segmentation and spatial reconstruction of infiltrated, collapsed, and emphysematous areas in lung CT.

Patient-specific reconstruction of volumetric computed tomography images from few-view projections via deep learning

3D Reconstruction from of 2D X-rays

CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging