End‐to‐end unsupervised cycle‐consistent fully convolutional network for 3D pelvic CT‐MR deformable registration
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.12968
Abstract: Abstract Objective To improve the efficiency of computed tomography (CT)‐magnetic resonance (MR) deformable image registration while ensuring the registration accuracy. Methods Two fully convolutional networks (FCNs) for generating spatial deformable grids were proposed using the… read more here.
Keywords: image; end; method; cycle consistent ... See more keywords
Compensation cycle consistent generative adversarial networks (Comp-GAN) for synthetic CT generation from MR scans with truncated anatomy.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16246
Abstract: BACKGROUND MR scans used in radiotherapy can be partially truncated due to the limited field of view, affecting dose calculation accuracy in MR-based radiation treatment planning. PURPOSE We proposed a novel Compensation-cycleGAN (Comp-cycleGAN) by modifying… read more here.
Keywords: truncated images; compensation; comp cyclegan; cycle consistent ... See more keywords
Unsupervised cycle‐consistent network using restricted subspace field map for removing susceptibility artifacts in EPI
Sign Up to like & getrecommendations! Published in 2023 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29653
Abstract: To design an unsupervised deep neural model for correcting susceptibility artifacts in single‐shot Echo Planar Imaging (EPI) and evaluate the model for preclinical and clinical applications. read more here.
Keywords: consistent network; network using; susceptibility; unsupervised cycle ... See more keywords
Cycle-Consistent Domain Adaptive Faster RCNN
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2938837
Abstract: Traditional object detection methods always assume both of the training and test data follow the same distribution, but this cannot always be guaranteed in the real world. Domain adaptive methods are proposed to handle this… read more here.
Keywords: cycle consistent; domain adaptive; consistent domain; source ... See more keywords
A Coherence-Guided InSAR Phase Unwrapping Method With Cycle-Consistent Adversarial Networks
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2023.3343517
Abstract: Phase unwrapping (PU) is a critical processing step for obtaining information on land surface deformation from interferometric synthetic aperture radar (InSAR) images. Traditional PU methods take the phase continuity assumption as the precondition. However, in… read more here.
Keywords: adversarial networks; cycle consistent; consistent adversarial; coherence ... See more keywords
Unsupervised Video Summarization With Cycle-Consistent Adversarial LSTM Networks
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2019.2959451
Abstract: Video summarization is an important technique to browse, manage and retrieve a large amount of videos efficiently. The main objective of video summarization is to minimize the information loss when selecting a subset of video… read more here.
Keywords: video; cycle consistent; video summarization; unsupervised video ... See more keywords
Semi-supervised Chinese poem-to-painting generation via cycle-consistent adversarial networks
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Electronic Imaging"
DOI: 10.1117/1.jei.33.5.053056
Abstract: Abstract. Classical Chinese poetry and painting represent the epitome of artistic expression, but the abstract and symbolic nature of their relationship poses a significant challenge for computational translation. Most existing methods rely on large-scale paired… read more here.
Keywords: adversarial networks; cycle consistent; semi supervised; supervised chinese ... See more keywords
SECCT: spectral-enhanced cycle-consistent transformer for hyperspectral image classification with few labeled samples
Sign Up to like & getrecommendations! Published in 2025 at "Optical Engineering"
DOI: 10.1117/1.oe.64.8.088102
Abstract: Abstract. In recent years, transformer-based methods have demonstrated strong potential in the classification of hyperspectral images (HSIs). However, most existing transformer models face challenges in HSI classification under scenarios with few labeled samples, such as… read more here.
Keywords: classification; labeled samples; cycle consistent; transformer ... See more keywords