ArticleIEEE transactions on medical imaging2015
3-D Adaptive Sparsity Based Image Compression With Applications to Optical Coherence Tomography.
Article in IEEE transactions on medical imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Convolutional dictionary learning for blind deconvolution of optical coherence tomography images.Biomedical optics express · 2022Article
- Deep OCT image compression with convolutional neural networks.Biomedical optics express · 2020Article
- Automatic detection of retinal regions using fully convolutional networks for diagnosis of abnormal maculae in optical coherence tomography images.Journal of biomedical optics · 2019Article
- Fast esophageal layer segmentation in OCT images of guinea pigs based on sparse Bayesian classification and graph search.Biomedical optics express · 2019Article
- Effect of three-dimensional reconstruction-assisted 23G micro-invasive vitrectomy in patients with proliferative diabetic retinopathy.Experimental and therapeutic medicine · 2017Article
- Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search.Biomedical optics express · 2017Article
- Segmentation Based Sparse Reconstruction of Optical Coherence Tomography Images.IEEE transactions on medical imaging · 2017Article
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Authors and funding
5 authors.
Funding
Abstract
We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods.
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