Recent developments in optical coherence tomography for imaging the retina.

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.

Speckle reduction in optical coherence tomography images using digital filtering.

Speckle noise significantly limits the information content provided by coherent optical imaging methods such as optical coherence tomography and its recent derivative, optical frequency-domain imaging (OFDI). In this paper, we demonstrate a novel OFDI system that simultaneously acquires hundreds of angularly resolved images, which can be compounded to reduce speckle noise. The system comprises an InGaAs line-scan camera and an interferometer, configured so that the elements of the detector array simultaneously capture light spanning a backscattering angular range of 32 degrees. On successive read-outs of the array, the wavelength of the laser source was stepped through a range of 130 nm centered at 1295 nm to concurrently generate 400 angle-resolved OFDI images. A theory of angle-resolved OFDI and the design equations of the system are presented. Incoherent averaging of the angle-resolved data is shown to yield substantial speckle reduction (as high as an 8 dB SNR improvement) in images of a tissue phantom and esophageal tissue ex vivo.

Speckle reduction in OCT using massively-parallel detection and frequency-domain ranging

We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and structure estimation. Based on this analysis, the wavelet detail coefficients are weighted, averaged and reconstructed. At a signal-to-noise gain at about 100% we observe only a minor sharpness decrease, as measured by a full-width-half-maximum reduction of 10.5%. While a similar signal-to-noise gain would require averaging of 29 frames, we achieve this result using only 8 frames as input to the algorithm. A possible application of the proposed algorithm is preprocessing in retinal structure segmentation algorithms, to allow a better differentiation between real tissue information and unwanted speckle noise.

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Wavelet denoising of multiframe optical coherence tomography data.

Speckle pattern, which is inherent in coherence imaging, influences significantly axial and transversal resolution of Optical Coherence Tomography (OCT) instruments. The well known speckle removal techniques are either sensitive to sample motion, require sophisticated and expensive sample tracking systems, or involve sophisticated numerical procedures. As a result, their applicability to in vivo real-time imaging is limited. In this work, we propose to average multiple A-scans collected in a fully controlled way to reduce the speckle contrast. This procedure involves non-coherent averaging of OCT A-scans acquired from adjacent locations on the sample. The technique exploits scanning protocol with fast beam deflection in the direction perpendicular to lateral dimension of the cross-sectional image. Such scanning protocol reduces the time interval between A-scans to be averaged to the repetition time of the acquisition system. Consequently, the averaging algorithm is immune to bulk motion of an investigated sample, does not require any sophisticated data processing to align cross-sectional images, and allows for precise control of lateral shift of the scanning beam on the object. The technique is tested with standard Spectral OCT system with an extra resonant scanner used for rapid beam deflection in the lateral direction. Ultrahigh speed CMOS camera serves as a detector and acquires 200,000 spectra per second. A dedicated A-scan generation algorithm allows for real-time display of images with reduced speckle contrast at 6 frames/second. This technique is applied to in vivo imaging of anterior and posterior segments of the human eye and human skin.

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Efficient reduction of speckle noise in Optical Coherence Tomography

For optical coherence tomography (OCT), ultrasound, synthetic-aperture radar, and other coherent ranging methods, speckle can cause spurious detail that detracts from the utility of the image. It is a problem inherent to imaging densely scattering objects with limited bandwidth. Using a method of regularization by minimizing Csiszar's I-divergence measure, we derive a method of speckle minimization that produces an image that both is consistent with the known data and extrapolates additional detail based on constraints on the magnitude of the image. This method is demonstrated on a test image and on an OCT image of a Xenopus laevis tadpole. © 2005 Optical Society of America OCIS codes: 100.3010, 110.4500. 2 (OCT), ultrasound, and synthetic-aperture radar. Natural objects usually contain detail at all scales, but most coherent ranging instruments can probe these details in only a narrow bandwidth of frequencies. The re- sult is speckle, which is caused by the seemingly random interference of scatterers within a resolution cell of the in- strument. Speckle randomizes the amplitudes of points in the image, which obscures fine features but generally al- lows coarse features to be resolved. We propose and dem- onstrate a method of regularization that removes these small-scale amplitude changes without smoothing the im- age. This is achieved by constraining the resulting recon- structed image to be consistent in a least-squares sense with the known data, while simultaneously utilizing Csiszar's I-divergence measure 3,4 to constrain and regu- larize the amplitudes of the reconstructed data. By ensur- ing that the resulting image is consistent with the known data, the detail is retained, while additional bandwidth is extrapolated to make the amplitudes of the image consis- tent with the regularization. Most natural objects, especially those biological in ori- gin, have detail at length scales from the macroscopic to the atomic. Unfortunately, because of instrument limita- tions and the attenutation of radiation by the sample, only a finite signal bandwidth can be utilized for useful resolution from the sample. The phenomenon of speckle in these imaging modalities is caused by the interference between scatterers that are too small and too close to- gether to be individually resolved. What is observed is a seemingly random modulation of the amplitude of the im- age as a result of the interference of scattered waves from these unresolved scatterers. Unfortunately, it is difficult in practice to differentiate between the features that are caused by the speckle modulation and the features of interest. Because scatter- ers are randomly placed in most natural objects, the coarse detail tends to be present in almost any frequency bandwidth that is much wider than the reciprocal of the minimum feature size one wishes to resolve. This is what enables most coherent ranging techniques to be used in practice. However, as one considers distinguishing fea- tures on the minimally resolvable scale of the instrument, it is less certain whether a certain feature is due to the random modulation of speckle or to scatterers with larger sizes.

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Danielâ L. Marks

Papers

Speckle reduction by I-divergence regularization in optical coherence tomography