My da|ra Login

Detailed view

metadata language: English

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

Version
V0
Resource Type
Dataset
Creator
  • Lakshminarayanan, Dr. Vasudevan (University of Waterloo)
Publication Date
2019-12-30
Funding Reference
  • NSERC CANADA DISCOVERY GRANT (VL)
Free Keywords
fundus; deep learning; retina; image synthesis; Generative Models
Description
  • Abstract

    This is a completely artificially generated dataset of fundus images with their corresponding blood vessel annotations.
    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)
Availability
Download

Update Metadata: 2020-01-20 | Issue Number: 1 | Registration Date: 2020-01-20

Lakshminarayanan, Dr. Vasudevan (2019): FunSyn-Net: Enhanced Residual Variational Auto-encoder and Image-to-Image Translation Network for Fundus Image Synthesis. Version: V0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E117290