[HTML][HTML] A review of generative adversarial network applications in optical coherence tomography image analysis
Optical coherence tomography (OCT) has revolutionized ophthalmic clinical practice and
research, as a result of the high-resolution images that the method is able to capture in a …
research, as a result of the high-resolution images that the method is able to capture in a …
[HTML][HTML] Enhanced OCT chorio-retinal segmentation in low-data settings with semi-supervised GAN augmentation using cross-localisation
Training deep learning methods for optical coherence tomography (OCT) retinal and
choroidal layer segmentation is a challenge when data is scarce. In medical image analysis …
choroidal layer segmentation is a challenge when data is scarce. In medical image analysis …
Segmenting medical images with limited data
While computer vision has proven valuable for medical image segmentation, its application
faces challenges such as limited dataset sizes and the complexity of effectively leveraging …
faces challenges such as limited dataset sizes and the complexity of effectively leveraging …
[HTML][HTML] Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and
choroidal layer segmentation in optical coherence tomography (OCT) images, require …
choroidal layer segmentation in optical coherence tomography (OCT) images, require …
Semi-supervised learning with cross-localisation in shared GAN latent space for enhanced OCT data augmentation
J Kugelman, D Alonso-Caneiro… - … on Digital Image …, 2022 - ieeexplore.ieee.org
Deep learning methods have demonstrated state-of-the-art performance for the
segmentation of the retina and choroid in optical coherence tomography (OCT) images …
segmentation of the retina and choroid in optical coherence tomography (OCT) images …