title: Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform.
abstract: ABSTRACT. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained.
authors.affiliation: University of Texas Medical Branch, Center for Biomedical Engineering, Galveston, Texas 77555, USA.
authors.forename: Shahab
authors.initials: S
authors.lastname: Chitchian
authors.forename: Markus A
authors.initials: MA
authors.lastname: Mayer
authors.forename: Adam R
authors.initials: AR
authors.lastname: Boretsky
authors.forename: Frederik J
authors.initials: FJ
authors.lastname: van Kuijk
authors.forename: Massoud
authors.initials: M
authors.lastname: Motamedi
mesh_terms: D000465:Algorithms; D003941:Diagnostic Techniques, Ophthalmological / Q000706:statistics & numerical data; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008268:Macular Degeneration / Q000473:pathology; D055620:Optical Phenomena; D012160:Retina / Q000033:anatomy & histology*; D059629:Signal-To-Noise Ratio; D041623:Tomography, Optical Coherence / Q000379:methods* / Q000706:statistics & numerical data; D058067:Wavelet Analysis