18 July 2016 Enhanced low-rank + sparsity decomposition for speckle reduction in optical coherence tomography
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Abstract
Speckle artifacts can strongly hamper quantitative analysis of optical coherence tomography (OCT), which is necessary to provide assessment of ocular disorders associated with vision loss. Here, we introduce a method for speckle reduction, which leverages from low-rank + sparsity decomposition (LRpSD) of the logarithm of intensity OCT images. In particular, we combine nonconvex regularization-based low-rank approximation of an original OCT image with a sparsity term that incorporates the speckle. State-of-the-art methods for LRpSD require
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Ivica Kopriva, Fei Shi, Xinjian Chen, "Enhanced low-rank + sparsity decomposition for speckle reduction in optical coherence tomography," Journal of Biomedical Optics 21(7), 076008 (18 July 2016). https://doi.org/10.1117/1.JBO.21.7.076008 . Submission:
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