Evgenia Bousi

Scatterer size-based analysis of optical coherence tomography images using spectral estimation techniques.

A novel spectral analysis technique of OCT images is demonstrated in this paper for classification and scatterer size estimation. It is based on SOCT autoregressive spectral estimation techniques and statistical analysis. Two different statistical analysis methods were applied to OCT images acquired from tissue phantoms, the first method required prior information on the sample for variance analysis of the spectral content. The second method used k-means clustering without prior information for the sample. The results are very encouraging and indicate that the spectral content of OCT signals can be used to estimate scatterer size and to classify dissimilar areas in phantoms and tissues with sensitivity and specificity of more than 90%.

Axial resolution improvement by modulated deconvolution in Fourier domain optical coherence tomography.

Abstract. A novel technique for axial resolution improvement in Fourier domain optical coherence tomography (FDOCT) is presented. The technique is based on the deconvolution of modulated optical coherence tomography signals. In FDOCT, the real part of the Fourier transform of the interferogram is modulated by a frequency which depends on the position of the interferogram in k space. A slight numerical k shift results in a different modulation frequency. By adding two shifted signals, beating can appear in the A-scan. When the amount of shifting is appropriately selected, deconvolution of the resulting depth profile, using suitable modulated kernels, yields a narrower resolution width. A resolution improvement by a factor of ∼7 can be achieved without the need for a broader bandwidth light source.

AM–FM techniques in the analysis of optical coherence tomography signals

The subtle tissue changes associated with the early stages of malignancies, such as cancer, are not clearly discernible even at the current, improved, resolution of optical coherence tomography (OCT) systems. However, these changes directly affect the spectral content of the OCT image that contains information regarding these unresolvable features. Spectral analysis of OCT signals has recently been shown to provide additional information, resulting in improved contrast, directly related to scatterer size changes. Amplitude modulation-frequency modulation (AM-FM) analysis, a fast and accurate technique for the estimation of the instantaneous frequency, phase, and amplitude of a signal, can also be applied to OCT images to extract scatterer-size information. The proposed technique could make available an extremely valuable tool for the investigation of disease characteristics that now remain below the resolution of OCT and could significantly improve the technologys diagnostic capabilities.

Optical coherence tomography axial resolution improvement by step-frequency encoding

A novel technique for axial resolution improvement of Optical Coherence Tomography (OCT) systems is proposed. The technique is based on step-frequency encoding, using frequency shifting, of the OCT signal. A resolution improvement by a factor of approximately 7 is achieved without the need for a broader bandwidth light source. This method exploits a combination of two basic principles: the appearance of beating, when adding two signals of slightly different carrier frequencies, and the resolution improvement by deconvolution of the interferogram with an encoded autocorrelation function. In time domain OCT, step-frequency encoding can be implemented by performing two scans, with different carrier frequencies, and subsequently adding them to create the encoded signal. When the frequency steps are properly selected, deconvolution of the resulting interferogram, using appropriate kernels, results in a narrower resolution width.

AM-FM Analysis of Optical Coherence Tomography Signals

The early stages of malignant diseases, such as cancer, are characterized by cellular and microstructural changes which define both the diagnosis and the prognosis of the disease. Unfortunately, at the current resolution of Optical Coherence Tomography (OCT), such changes associated with early cancer are not clearly discernible. However, spectral analysis of OCT images has recently shown that additional information can be extracted from those signals, resulting in improved contrast which is directly related to scatterer size changes. Amplitude Modulation - Frequency Modulation (AM-FM) analysis is a fast and accurate technique which can also be applied to the OCT images for estimation of spectral information. It is based on the analytic signal of the real data, obtained using a Hilbert Transform, and provides the instantaneous amplitude, phase, and frequency of an OCT signal. The performance of this method is superior to both FFT-based and parametric (e.g. autoregressive) spectral analysis providing better accuracy and faster convergence when estimating scatterer features. Since disease tissues exhibit variations in scatterer size and thus also exhibit marked differences in spectral and phase characteristics, such advanced analysis techniques can provide more insight into the subtle changes observed in OCT images of malignancy. Therefore, they can make available a tool which could prove extremely valuable for the investigation of disease features which now remain below the resolution of OCT and improved the technologys diagnostic capabilities.

Using speckle to measure tissue dispersion in optical coherence tomography

In Optical Coherence tomography (OCT), dispersion mismatches cause degradation of the image resolution. However, dispersion is specific to the material that is causing the effect and can therefore carry useful information regarding the composition of the samples. In this summary, we propose a novel technique for estimating the dispersion in tissue which uses the image speckle to calculate the PSF degradation and is therefore applicable to any tissue and can be implemented in vivo and in situ. A Wiener-type deconvolution algorithm was used to estimate the image PSF degradation from the speckle. The proposed method was verified ex vivo resulting in comparable values of the Group Velocity Dispersion (GVD) as obtained by a standard estimation technique described in the literature. The applicability to cancer diagnosis was evaluated on a small set of gastrointestinal normal and cancer OCT images. Using the statistics of the GVD estimate, the tissue classification resulted in 93% sensitivity and 73% specificity (84% correct classification rate). The success of these preliminary results indicates the potential of the proposed method which should be further investigated to elucidate its advantages and limitations.

Correlation of the derivative as a robust estimator of scatterer size in optical coherence tomography (OCT) [Invited]

The size-dependent spectral variations, predicted by Mie theory, have already been considered as a contrast enhancement mechanism in optical coherence tomography. In this work, a new spectroscopic metric, the bandwidth of the correlation of the derivative, was developed for estimating scatterer size which is more robust and accurate compared to existing methods. Its feasibility was demonstrated using phantoms containing polystyrene microspheres as well as images of normal and cancerous human colon. The results are very promising, suggesting that the proposed metric could be utilized for measuring nuclear size distribution, a diagnostically valuable marker, in human tissues.

Lateral resolution improvement in oversampled optical coherence tomography images assuming weighted oversampled multi-scatterer contributions

A novel method for lateral resolution improvement of Optical Coherence Tomography (OCT) images, which is independent of the focusing of the delivery optics and the depth of field, is presented. This method was inspired by radar range oversampling techniques. It is based on the lateral oversampling of the image and the estimation of the locations of the multiple scatterers which contribute to the signal. The information in the oversampled images is used to estimate the locations of multiple scatterers assuming each contributes a weighted portion to the detected signal, the weight determined by the location of the scatterer and the point spread function (PSF) of the system. A priori knowledge of the PSF is not required since optimization techniques can be employed to achieve the best possible enhancement of the image resolution. Preliminary results of such an approach on laterally oversampled OCT images have shown that it is possible to achieve a two-fold lateral resolution improvement. Moreover by performing deconvolution with the new improved PSF the lateral resolution can be further improved by another factor of two for a total of 4x improvement. Such improvement can be significant, especially in cases where the Numerical Aperture (NA) of the delivery optics is limited, such as, for example, in the case of ophthalmic imaging where the optics of the eye itself limit the lateral resolution.

AM-FM Techniques in Optical Coherence Tomography

The early stages of malignant diseases, such as cancer, are characterized by cellular and microstructural changes which define both the diagnosis and the prognosis of the disease. Unfortunately, at the current resolution of Optical Coherence Tomography (OCT), such changes associated with early cancer are not clearly discernible. However, spectral analysis of OCT images has recently shown that additional information can be extracted from those signals, resulting in improved contrast which is directly related to scatterer size changes. Amplitude Modulation - Frequency Modulation (AM-FM) analysis is a fast and accurate technique which can also be applied to the OCT images for estimation of spectral information. It is based on the analytic signal of the real data, obtained using a Hilbert Transform, and provides the instantaneous amplitude, phase, and frequency of an OCT signal. The performance of this method is superior to both FFT-based and parametric (e.g. autoregressive) spectral analysis providing better accuracy and faster convergence when estimating scatterer features. Since disease tissues exhibit variations in scatterer size and thus also exhibit marked differences in spectral and phase characteristics, such advanced analysis techniques can provide more insight into the subtle changes observed in OCT images of malignancy. Therefore, they can make available a tool which could prove extremely valuable for the investigation of disease features which now remain below the resolution of OCT and improved the technologys diagnostic capabilities.

Wavelet decomposition for speckle reduction with feature preservation in optical coherence tomography

Optical Coherence Tomography (OCT) images exhibit the effects of speckle which can make image interpretation and quantitative measurements difficult. Many approaches have been developed to reduce this speckle including both hardware implementations and post-processing techniques. However, they either suffer from a loss in resolution and blurring of the image or an increase in complexity and reduction in speed of the system. Wavelet decomposition has been shown to effectively separate the resolvable features of an image from the speckle pattern. The two components can then be processed separately. The speckle pattern can be filtered and then recombined with the resolvable component to create an image with improved signal-to-noise-ratio (SNR) and intact image details. The results of this algorithm are demonstrated on in vivo OCT images of skin taken with a swept-source based system. Such a technique, when applied, for example, to OCT images of disease, can be extremely useful in improving the clinical interpretation of the images as well as allowing more accurate quantitative measurements not affected by the presence of speckle.