ArticleIEEE transactions on medical imaging2017
Segmentation Based Sparse Reconstruction of Optical Coherence Tomography Images.
Article in IEEE transactions on medical imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Hybrid method and CNN regressor for OCT images to predict visual acuity of retinal occlusion patients after 12 months of treatment.Medical & biological engineering & computing · 2026Article
- Retinal OCT image classification based on MGR-GAN.Medical & biological engineering & computing · 2025Article
- A Survey on Optical Coherence Tomography-Technology and Application.Bioengineering (Basel, Switzerland) · 2025Review
- Self-supervised Self2Self denoising strategy for OCT speckle reduction with a single noisy image.Biomedical optics express · 2024Article
- Unpaired intra-operative OCT (iOCT) video super-resolution with contrastive learning.Biomedical optics express · 2024Article
- Speckle contrast reduction through the use of a modally-specific photonic lantern for optical coherence tomography.Biomedical optics express · 2023Article
- Self-supervised Blind2Unblind deep learning scheme for OCT speckle reductions.Biomedical optics express · 2023Article
- Mixed multiscale BM4D for three-dimensional optical coherence tomography denoising.Computers in biology and medicine · 2023Article
- Review
- Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.IEEE transactions on bio-medical engineering · 2022Article
- Self-supervised patient-specific features learning for OCT image classification.Medical & biological engineering & computing · 2022Article
- Retinal optical coherence tomography image analysis by a restricted Boltzmann machine.Biomedical optics express · 2022Article
- Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images.Experimental eye research · 2022Article
- Intra-operative OCT (iOCT) Super Resolution: a Two-Stage Methodology Leveraging High Quality Pre-operative OCT Scans.Ophthalmic medical image analysis : 9th International Workshop, OMIA 2022, Held in Conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, Proceedings. OMIA (Workshop) (9th : 2022 : Singapore, Singapore) · 2022Article
- Resolution enhancement and realistic speckle recovery with generative adversarial modeling of micro-optical coherence tomography.Biomedical optics express · 2020Article
- 3D Shape Modeling and Analysis of Retinal Microvasculature in OCT-Angiography Images.IEEE transactions on medical imaging · 2020Article
- Optical coherence refraction tomography.Nature photonics · 2019Article
- Automatic detection of retinal regions using fully convolutional networks for diagnosis of abnormal maculae in optical coherence tomography images.Journal of biomedical optics · 2019Article
- Automated drosophila heartbeat counting based on image segmentation technique on optical coherence tomography.Scientific reports · 2019Article
- Fast esophageal layer segmentation in OCT images of guinea pigs based on sparse Bayesian classification and graph search.Biomedical optics express · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We demonstrate the usefulness of utilizing a segmentation step for improving the performance of sparsity based image reconstruction algorithms. In specific, we will focus on retinal optical coherence tomography (OCT) reconstruction and propose a novel segmentation based reconstruction framework with sparse representation, termed segmentation based sparse reconstruction (SSR). The SSR method uses automatically segmented retinal layer information to construct layer-specific structural dictionaries. In addition, the SSR method efficiently exploits patch similarities within each segmented layer to enhance the reconstruction performance. Our experimental results on clinical-grade retinal OCT images demonstrate the effectiveness and efficiency of the proposed SSR method for both denoising and interpolation of OCT images.
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