Generative adversarial network for super-resolution imaging through a fiber
A multimode fiber represents the ultimate limit in miniaturization of imaging endoscopes. Here we propose a fiber imaging approach employing compressive sensing with a data-driven machine learning framework. We implement a generative adversarial network for image reconstruction without relying on a sample sparsity constraint. The proposed method outperforms the conventional compressive imaging algorithms in terms of image quality and noise robustness. We experimentally demonstrate speckle-based imaging below the diffraction limit at a sub-Nyquist speed through a multimode fiber.
Code (0)
등록된 구현이 없습니다.
Tasks
Compressive SensingGenerative Adversarial NetworkImage ReconstructionSuper-ResolutionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Images
Because of the necessity to obtain high-quality images with minimal radiation doses, such as in low-field magnetic resonance imaging, super-resolution reconstruction in medical imaging has become more popular (MRI). Howe…
Generative Adversarial NetworkImage Super-ResolutionSSIMSuper-ResolutionJoint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation
Optimising the analysis of cardiac structure and function requires accurate 3D representations of shape and motion. However, techniques such as cardiac magnetic resonance imaging are conventionally limited to acquiring c…
Domain AdaptationDomain GeneralizationGenerative Adversarial NetworkSuper-ResolutionMedSRGAN: medical images super-resolution using generative adversarial networks
Super-resolution (SR) in medical imaging is an emerging application in medical imaging due to the needs of high quality images acquired with limited radiation dose, such as low dose Computer Tomography (CT), low field …
Super-ResolutionSuper Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network
Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is a powerful imaging technology that can measure cerebral blood flow (CBF) quantitatively. However, since only a small portion of blood is labeled compared t…
Generative Adversarial NetworkSSIMSuper-ResolutionHigh-throughput, high-resolution registration-free generated adversarial network microscopy
We combine generative adversarial network (GAN) with light microscopy to achieve deep learning super-resolution under a large field of view (FOV). By appropriately adopting prior microscopy data in an adversarial trainin…
Generative Adversarial NetworkImage RegistrationImage Super-ResolutionSuper-Resolution+1