Farzana Zaki

Nonlinear characterization of elasticity using quantitative optical coherence elastography.

Optical coherence elastography (OCE) has been used to perform mechanical characterization on biological tissue at the microscopic scale. In this work, we used quantitative optical coherence elastography (qOCE), a novel technology we recently developed, to study the nonlinear elastic behavior of biological tissue. The qOCE system had a fiber-optic probe to exert a compressive force to deform tissue under the tip of the probe. Using the space-division multiplexed optical coherence tomography (OCT) signal detected by a spectral domain OCT engine, we were able to simultaneously quantify the probe deformation that was proportional to the force applied, and to quantify the tissue deformation. In other words, our qOCE system allowed us to establish the relationship between mechanical stimulus and tissue response to characterize the stiffness of biological tissue. Most biological tissues have nonlinear elastic behavior, and the apparent stress-strain relationship characterized by our qOCE system was nonlinear an extended range of strain, for a tissue-mimicking phantom as well as biological tissues. Our experimental results suggested that the quantification of force in OCE was critical for accurate characterization of tissue mechanical properties and the qOCE technique was capable of differentiating biological tissues based on the elasticity of tissue that is generally nonlinear.

Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography

Optical coherence tomography (OCT) is based on coherence detection of interferometric signals and hence inevitably suffers from speckle noise. To remove speckle noise in OCT images, wavelet domain thresholding has demonstrated significant advantages in suppressing noise magnitude while preserving image sharpness. However, speckle noise in OCT images has different characteristics in different spatial scales, which has not been considered in previous applications of wavelet domain thresholding. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) algorithm that exploits the difference of noise characteristics in different wavelet sub-bands. The algorithm is simple, fast, effective and is closely related to the physical origin of speckle noise in OCT image. Our results demonstrate that NAWT outperforms conventional wavelet thresholding.

High-definition optical coherence tomography imaging for noninvasive examination of heritage works

Cultural heritage works, such as ancient murals and historical paintings, are examined routinely for the purpose of conservation. Previous works have applied optical coherence tomography (OCT), which is a three-dimensional (3D) microscopic imaging modality in the field of heritage works conservation. The data acquired by OCT provides both 3D surface information of the object and structure information underneath the surface. Therefore, cross-sectional information on the object can be utilized to study layer structure of the painting and brush stroke techniques used by the artist. However, as demonstrated in previous studies, OCT has limited capability in high-definition (HD) examination of paintings or murals that are in macroscopic scale. HD examination of heritage works needs to scan large areas and process huge amounts of data, while OCT imaging has a limited field of view and processing power. To further advance the application of OCT in the conservation of heritage works, we demonstrate what we believe is a novel high-speed, large field-of-view (FOV) OCT imaging platform. Our results suggest that this OCT platform has the potential to become a nondestructive alternative for the analysis and conservation of paintings and murals.

Quantitative Optical Coherence Elastography for Robust Stiffness Assessment

We demonstrated the capability of quantitative optical coherence elastography (qOCE) for robust assessment of material stiffness under different boundary conditions using the reaction force and displacement field established in the sample.

Assessment and removal of additive noise in a complex optical coherence tomography signal based on Doppler variation analysis

In this study, we investigate and validate a novel approach to assess and remove additive noise for optical coherence tomography (OCT) imaging. Our method first generates a map of additive noise for the OCT image through Doppler variation analysis. We then remove the additive noise from the real and imaginary parts of the complex OCT signal through pixelwise Wiener filtering. Our results show that the method described in this manuscript improves the sensitivity of OCT imaging and preserves the spatial resolution without the need to modify the imaging apparatus and data acquisition protocol.

Characterization of nonlinear elasticity for biological tissue using quantitative optical coherence elastography

We developed a quantitative optical coherence elastography (qOCE) system for nonlinear mechanical characterization of biological tissues. The fiber-optic probe of the qOCE system had an integrated Fabry-Perot force sensor. To perform mechanical characterization, the tissue was compressed uniaxially by the fiber-optic probe of the qOCE system. Using the optical coherence tomography (OCT) signal detected by a spectral domain OCT engine, we were able to simultaneously quantify the force exerted to the tissue and the displacement of tissue. The quantification of the force was critical for accurate assessment of the elastic behavior of tissue, because most biological tissues have nonlinear elastic behavior. We performed qOCE characterization on tissue mimicking phantoms and biological tissues. Our results demonstrated the capability of the qOCE system for linear and nonlinear assessment of tissue elasticity.

Optical coherence tomography for non-invasive examination and conservation of cultural heritage objects

Optical coherence tomography (OCT) has great potential for the examination of oil paintings, particularly for celebrated masterpieces by great artists in history. We developed an OCT system for large field of view (FOV), high definition (HD) imaging of oil paintings. To achieve large FOV, we translated the sample using a pair of high-precision linear motors and performed sequential volumetric imaging on adjacent, non-overlapping regions. Through 3D OCT imaging, the surface terrain and subsurface microarchitecture of the paintings have been characterized and visualized.

Depth resolved optical coherence elastography based on fiber-optic probe with integrated Fabry-Perot force sensor

We performed depth resolved elasticity measurement based on a quantitative optical coherence elastography system with integrated Fabry-Perot force sensor. We performed depth resolved stiffness measurement on a muti-layer phantom under different axial force.

Entropy analysis of OCT signal for automatic tissue characterization

Optical coherence tomography (OCT) signal can provide microscopic characterization of biological tissue and assist clinical decision making in real-time. However, raw OCT data is noisy and complicated. It is challenging to extract information that is directly related to the pathological status of tissue through visual inspection on huge volume of OCT signal streaming from the high speed OCT engine. Therefore, it is critical to discover concise, comprehensible information from massive OCT data through novel strategies for signal analysis. In this study, we perform Shannon entropy analysis on OCT signal for automatic tissue characterization, which can be applied in intraoperative tumor margin delineation for surgical excision of cancer. The principle of this technique is based on the fact that normal tissue is usually more structured with higher entropy value, compared to pathological tissue such as cancer tissue. In this study, we develop high-speed software based on graphic processing units (GPU) for real-time entropy analysis of OCT signal.