Speckle reduction by I-divergence regularization in optical coherence tomography

Marks, D.L.; Ralston, Tylerâ S.; Boppart, Stephen A.

doi:10.1364/josaa.22.002366

Cited by 83 publications

(53 citation statements)

References 25 publications

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“…Optical coherence tomography (OCT) is a promising technology for imaging the microscopic structure of human tissue in vivo [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. Owing to the coherent nature of the image formation process, OCT images suffer from speckle noise.…”

Section: Introductionmentioning

confidence: 99%

“…Speckle reduction in OCT has been addressed by modifying imaging configurations and through the use of signal processing. Recently, some digital algorithms [6,9,12,13] have been applied to OCT images with encouraging results. Optical approaches that physically reduce speckle by incoherent averaging (compounding) have also been demonstrated [5,8,10,14].…”

Section: Introductionmentioning

confidence: 99%

“…Filter performance was evaluated using established speckle-reduction performance metrics [6,9,12,13], including SNR, contrast-tonoise ratio (CNR), and equivalent number of looks (ENL), which is a measure of the smoothness of a homogeneous region of interest. The following definitions for these image quality metrics were used [6,9,12,13]: (1) where F lin is the linear magnitude image, is the variance of F lin in a background noise region, μ b and are the mean and variance of the same background noise region, μ h and are the mean and variance of all the homogeneous regions of interest (H), and finally μ r and are the mean and variance of all the regions of interests (R), including the homogeneous regions (H). Following earlier work [12], except for the SNR calculations, all the other parameters were computed from the logarithmic OCT images.…”

Section: Introductionmentioning

confidence: 99%

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Speckle reduction in optical coherence tomography images using digital filtering

et al. 2007

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Speckle noise is a ubiquitous artifact that limits the interpretation of optical coherence tomography images. Here we apply various speckle-reduction digital filters to optical coherence tomography images and compare their performance. Our results indicate that shift-invariant, nonorthogonal wavelet-transform-based filters together with enhanced Lee and adaptive Wiener filters can significantly reduce speckle and increase the signal-to-noise ratio, while preserving strong edges. The speckle reduction capabilities of these filters are also compared with speckle reduction from incoherent angular compounding. Our results suggest that by using these digital filters, the number of individual angles required to attain a certain level of speckle reduction can be decreased.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Speckle reduction in optical coherence tomography images using digital filtering

et al. 2007

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“…Whilst digital image processing methods [2][3] have met with some success, they are fundamentally limited by their reliance on statistical relationships between neighboring pixels. As such, they typically involve a compromise between the extent of speckle reduction and the loss in spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Angle-resolved Optical Coherence Tomography with sequential angular selectivity for speckle reduction

Desjardins¹,

Vakoc²,

Oh³

et al. 2007

Opt. Express

121

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We present a novel method for rapidly acquiring optical coherence tomography (OCT) images at multiple backscattering angles. By angularly compounding these images, high levels of speckle reduction were achieved. Signal-to-noise ratio (SNR) improvements of 3.4 dB were obtained from a homogeneous tissue phantom, which was in good agreement with the predictions of a statistical model of speckle that incorporated the optical parameters of the imaging system. In addition, the fast acquisition rate of the system (10 kHz A-line repetition rate) allowed angular compounding to be performed in vivo without significant motion artifacts. Speckle-reduced OCT images of human dermis show greatly improved delineation of tissue microstructure.

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“…Rogowska and Brezinski [4] adopted the rotating kernel transformation technique to the speckle reduction and enhancement of OCT images, which was based on sequential application of directional masks and the selection of the maximum of all outputs. I-divergence regularization [12] was used to despeckle and retain the detail of the original data. This method produced a synthesized complex amplitude image that constrained the complex data to be consistent with the measured data in a least-squares sense, but also manipulated the magnitudes of the complex data to the degree allowed by measurement error.…”

Section: Introductionmentioning

confidence: 99%

Application of Improved Homogeneity Similarity-Based Denoising in Optical Coherence Tomography Retinal Images

et al. 2014

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Image denoising is a fundamental preprocessing step of image processing in many applications developed for optical coherence tomography (OCT) retinal imaging-a highresolution modality for evaluating disease in the eye. To make a homogeneity similarity-based image denoising method more suitable for OCT image removal, we improve it by considering the noise and retinal characteristics of OCT images in two respects: (1) median filtering preprocessing is used to make the noise distribution of OCT images more suitable for patchbased methods; (2) a rectangle neighborhood and region restriction are adopted to accommodate the horizontal stretching of retinal structures when observed in OCT images. As a performance measurement of the proposed technique, we tested the method on real and synthetic noisy retinal OCT images and compared the results with other well-known spatial denoising methods, including bilateral filtering, five partial differential equation (PDE)-based methods, and three patchbased methods. Our results indicate that our proposed method seems suitable for retinal OCT imaging denoising, and that, in general, patch-based methods can achieve better visual denoising results than point-based methods in this type of imaging, because the image patch can better represent the structured information in the images than a single pixel. However, the time complexity of the patch-based methods is substantially higher than that of the others.

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Speckle reduction by I-divergence regularization in optical coherence tomography

Cited by 83 publications

References 25 publications

Speckle reduction in optical coherence tomography images using digital filtering

Speckle reduction in optical coherence tomography images using digital filtering

Angle-resolved Optical Coherence Tomography with sequential angular selectivity for speckle reduction

Application of Improved Homogeneity Similarity-Based Denoising in Optical Coherence Tomography Retinal Images

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