使用最先进的卷积神经网络架构,包括3D UNet、3D VNet和2D UNet进行脑肿瘤分割,并使用分割的图像特征通过深度神经网络进行患者生存预测。
unet-architecture 开源项目推荐(5 个)
unet-architecture 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 全部 5
GitHub 共 5 个仓库,已全部展示The project involves using a dataset of 100 high-resolution retinal fundus images for blood vessel segmentation to aid in early detection of retinal pathologies | Implemented U-Net architecture from scratch, known for its efficiency in semantic segmentation with limited data | The final model achieved 86% IoU score | PyTorch Lightning
Development of a depth estimation model based on a UNET architecture - connection of Bi-directional Feature Pyramid Network (BIFPN) and EfficientNet.
Dual-AttnGAN: A dual-input GAN for joint low-light image enhancement and 4× super-resolution, fusing wide-angle and zoomed images via asymmetric cross-attention.
This project is an AI-powered Medical Image Super-Resolution system designed to enhance the quality of low-resolution X-ray and MRI images using a U-Net deep learning architecture. Built with TensorFlow, Keras, OpenCV, and Flask, the system reconstructs high-resolution images while preserving important anatomical details.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 5 个项目;原始页面见 https://github.com/topics/unet-architecture。
- 该话题在 GitHub 上共有 5 个仓库, 本站收录的是其中最热门的 5 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 5 个项目累计 181 Star,覆盖 2 种主要语言,数据更新于 2026-11-10。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。