1. Semi-Supervised Automatic Segmentation of Layer and Fluid Region in Retinal Optical Coherence Tomography Images Using Adversarial Learning

    Semi-Supervised Automatic Segmentation of Layer and Fluid Region in Retinal Optical Coherence Tomography Images Using Adversarial Learning

    Optical coherence tomography (OCT) is a primary imaging technique for ophthalmic diagnosis due to its advantages in high resolution and non-invasiveness. Diabetes is a chronic disease, which could cause retinal layer deformation and fluid accumulation. It might increase the risk of blindness, and thus, it is important to monitor the morphology change of the retinal layer and fluid accumulation for diabetes patients. Due to the existence of deformation and fluid accumulation, the retinal layer and fluid region segmentation in the OCT image is a challenging task. Machine learning-based segmentation methods have been proposed, but they depend on a significant number ...

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