Showing eess.IVShow all
3 papers · 1 filter
eess.IV2022
GAN-based Super-Resolution and Segmentation of Retinal Layers in Optical coherence tomography Scans
Paria Jeihouni, Omid Dehzangi, Annahita Amireskandari +2
In this paper, we design a Generative Adversarial Network (GAN)-based solution for super-resolution and segmentation of optical coherence tomography (OCT) scans of the retinal laye…
eess.IV2022
Superresolution and Segmentation of OCT scans using Multi-Stage adversarial Guided Attention Training
Paria Jeihouni, Omid Dehzangi, Annahita Amireskandari +3
Optical coherence tomography (OCT) is one of the non-invasive and easy-to-acquire biomarkers (the thickness of the retinal layers, which is detectable within OCT scans) being inves…
eess.IV2020
Efficient OCT Image Segmentation Using Neural Architecture Search
Saba Heidari Gheshlaghi, Omid Dehzangi, Ali Dabouei +3
In this work, we propose a Neural Architecture Search (NAS) for retinal layer segmentation in Optical Coherence Tomography (OCT) scans. We incorporate the Unet architecture in the…