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Found 3 papers, 1 papers with code
SAMedOCT: Adapting Segment Anything Model (SAM) for Retinal OCT
The Segment Anything Model (SAM) has gained significant attention in the field of image segmentation due to its impressive capabilities and prompt-based interface.
Segmentation of Bruch's Membrane in retinal OCT with AMD using anatomical priors and uncertainty quantification
Bruch's membrane (BM) segmentation on optical coherence tomography (OCT) is a pivotal step for the diagnosis and follow-up of age-related macular degeneration (AMD), one of the leading causes of blindness in the developed world.
SD-LayerNet: Semi-supervised retinal layer segmentation in OCT using disentangled representation with anatomical priors
Optical coherence tomography (OCT) is a non-invasive 3D modality widely used in ophthalmology for imaging the retina.
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