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Found 4 papers, 1 papers with code
Multi-scale Sparse Representation-Based Shadow Inpainting for Retinal OCT Images
To address these challenges, we propose a novel multi-scale shadow inpainting framework for OCT images by synergically applying sparse representation and deep learning: sparse representation is used to extract features from a small amount of training images for further inpainting and to regularize the image after the multi-scale image fusion, while convolutional neural network (CNN) is employed to enhance the image quality.
Frequency-Aware Physics-Inspired Degradation Model for Real-World Image Super-Resolution
In particular, we propose to use a convolutional neural network (CNN) to learn the cutoff frequency of real-world degradation process.
Multi-scale GCN-assisted two-stage network for joint segmentation of retinal layers and disc in peripapillary OCT images
An accurate and automated tissue segmentation algorithm for retinal optical coherence tomography (OCT) images is crucial for the diagnosis of glaucoma.
Medical Image Segmentation
Retinal OCT Layer Segmentation
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1.23-Tb/s per Wavelength Single-Waveguide On-Chip Optical Interconnect Enabled by Mode-division Multiplexing
We experimentally demonstrate a record net capacity per wavelength of 1. 23~Tb/s over a single silicon-on-insulator (SOI) multimode waveguide for optical interconnects employing on-chip mode-division multiplexing and 11$\times$11 multiple-in-multiple-out (MIMO) digital signal processing.
