OCTAGAN OCTA Quality Assessment

The WebApp will score the degree of artifact in the 3D OCTA volumes into “Good” or “Suboptimal”. This is based on a neural network algorithm, OCTA-GAN.

Usage: Drag and drop 3mm x 3mm Zeiss OCTA .img files into the gray box. Depending on the computer you could select up to approximately 30 at a time.

Drag & drop, or click to browse...

Output Data

References:

  1. Sumpena E, Kashani AH, Jones C, “Unsupervised Artifact Detection in 3D OCTA Microvascular Imaging based on Generative Adversarial Networks”, Annual ARVO meeting in Seattle WA, Poster A0216, May 6, 2024.
  2. Jones C, Sumpena E, Cornelio A, Seshadri S, Beiser A, Kashani AH, “Quantitative Study on the Generalizability of 3D OCTA Artifact Detection with OCTA-GAN”, Annual ARVO meeting in Salt Lake City UT, Poster A107, May 5, 2025.