Inpainting for Saturation Artifacts in Optical Coherence Tomography Using Dictionary-Based Sparse Representation

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dc.contributor.authorLiu, Hongshan
dc.contributor.authorCao, Shengting
dc.contributor.authorLing, Yuye
dc.contributor.authorGan, Yu
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.contributor.otherShanghai Jiao Tong University
dc.date.accessioned2023-09-28T19:33:27Z
dc.date.available2023-09-28T19:33:27Z
dc.date.issued2021
dc.description.abstractSaturation artifacts in optical coherence tomography (OCT) occur when received signal exceeds the dynamic range of spectrometer. Saturation artifact shows a streaking pattern and could impact the quality of OCT images, leading to inaccurate medical diagnosis. In this paper, we automatically localize saturation artifacts and propose an artifact correction method via inpainting. We adopt a dictionary-based sparse representation scheme for inpainting. Experimental results demonstrate that, in both case of synthetic artifacts and real artifacts, our method outperforms interpolation method and Euler's elastica method in both qualitative and quantitative results. The generic dictionary offers similar image quality when applied to tissue samples which are excluded from dictionary training. This method may have the potential to be widely used in a variety of OCT images for the localization and inpainting of the saturation artifacts.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationLiu, H., Cao, S., Ling, Y., & Gan, Y. (2021). Inpainting for Saturation Artifacts in Optical Coherence Tomography Using Dictionary-Based Sparse Representation. In IEEE Photonics Journal (Vol. 13, Issue 2, pp. 1–10). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/jphot.2021.3056574
dc.identifier.doi10.1109/JPHOT.2021.3056574
dc.identifier.orcidhttps://orcid.org/0000-0002-4628-7604
dc.identifier.orcidhttps://orcid.org/0000-0003-3409-3412
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11413
dc.languageEnglish
dc.language.isoen_US
dc.publisherIEEE
dc.subjectDictionaries
dc.subjectTraining
dc.subjectMachine learning
dc.subjectOptical coherence tomography
dc.subjectLicenses
dc.subjectInterpolation
dc.subjectImage reconstruction
dc.subjectInpainting
dc.subjectoptical coherence tomography
dc.subjectsaturation artifacts
dc.subjectsparse representation
dc.subjectEngineering, Electrical & Electronic
dc.subjectOptics
dc.subjectPhysics, Applied
dc.titleInpainting for Saturation Artifacts in Optical Coherence Tomography Using Dictionary-Based Sparse Representationen_US
dc.typeArticle
dc.typetext
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