FunSyn-Net: Enhanced Residual Variational Auto-encoder and Image-to-Image Translation Network for Fundus Image Synthesis

Name: FunSyn-Net: Enhanced Residual Variational Auto-encoder and Image-to-Image Translation Network for Fundus Image Synthesis
Creator: University of Waterloo
Published: 2019-01-01T00:00:00+08:00

ICPSR2019-01-01 更新2026-04-16 收录

口腔医学图像合成

眼底图像生成

数据链接：

https://www.openicpsr.org/openicpsr/project/117290/version/V1/view 数据链接链接失效反馈

官方服务：

资源简介：

This is a completely artificially generated dataset of fundus images with their corresponding blood vessel annotations. <br>Please use the following citation if you use the database "S. Sengupta, A. Athwale, T. Gulati, J. Zelek, V. Lakshminarayanan, FunSyn-Net: Enhanced Residual Variational Auto-encoder and Image-to-Image Translation Network for Fundus Image Synthesis, SPIE Medical Imaging, Houston, US, 2020( To be appeared)<br>

提供机构：

University of Waterloo

创建时间：

2019-01-01