Denoising diffusion models, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

Denoising diffusion models, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

Optical coherence tomography (OCT) is a prevalent non-invasive imaging method which
provides high resolution volumetric visualization of retina. However, its inherent defect, the …

Optical coherence tomography (OCT) has become the gold standard for ophthalmic
diagnostic imaging. However, clinical OCT image-quality is highly variable and limited …

Optical coherence tomography (OCT) is a non-invasive imaging technique widely used for
ophthalmology. It can be extended to OCT angiography (OCT-A), which reveals the retinal …

Abstract Domain generalization has great impact on medical image analysis as data
distribution inconsistencies are prevalent in most of the medical data modalities due to the …

Imaging from optical coherence tomography (OCT) is widely used for detecting retinal
diseases, localization of intra-retinal boundaries, etc. It is, however, degraded by speckle …

We present a deep learning framework for volumetric speckle reduction in optical coherence
tomography (OCT) based on a conditional generative adversarial network (cGAN) that …

The application of Diffusion Models in Medical Imaging has emerged as a promising
approach to enhance diagnostic and prognostic capabilities. This blog post will present a …