Skull's Photoacoustic Attenuation and Dispersion Modeling with Deterministic Ray-Tracing: Towards Real-Time Aberration Correction.

Although transcranial photoacoustic imaging has been previously investigated by several groups, there are many unknowns about the distorting effects of the skull due to the impedance mismatch between the skull and underlying layers. The current computational methods based on finite-element modeling are slow, especially in the cases where fine grids are defined for a large 3-D volume. We develop a very fast modeling/simulation framework based on deterministic ray-tracing. The framework considers a multilayer model of the medium, taking into account the frequency-dependent attenuation and dispersion effects that occur in wave reflection, refraction, and mode conversion at the skull surface. The speed of the proposed framework is evaluated. We validate the accuracy of the framework using numerical phantoms and compare its results to k-Wave simulation results. Analytical validation is also performed based on the longitudinal and shear wave transmission coefficients. We then simulated, using our method, the major skull-distorting effects including amplitude attenuation, time-domain signal broadening, and time shift, and confirmed the findings by comparing them to several ex vivo experimental results. It is expected that the proposed method speeds up modeling and quantification of skull tissue and allows the development of transcranial photoacoustic brain imaging.

Simulated annealing optimization in wavefront shaping controlled transmission.

In this research, we present results of simulated annealing (SA), a heuristic optimization algorithm, for focusing light through a turbid medium. Performance of the algorithm on phase and amplitude modulations has been evaluated. A number of tips to tune the optimization parameters are provided. The effect of measurement noise on the performance of the SA algorithm is explored. Additionally, SA performance is compared with continuous sequential and briefly with other optimization algorithms.

Low Temperature-Mediated Enhancement of Photoacoustic Imaging Depth.

We study the temperature dependence of the underlying mechanisms related to the signal strength and imaging depth in photoacoustic imaging. The presented theoretical and experimental results indicate that imaging depth can be improved by lowering the temperature of the intermediate medium that the laser passes through to reach the imaging target. We discuss the temperature dependency of optical and acoustic properties of the intermediate medium and their changes due to cooling. We demonstrate that the SNR improvement of the photoacoustic signal is mainly due to the reduction of Grüneisen parameter of the intermediate medium which leads to a lower level of background noise. These findings may open new possibilities toward the application of biomedical laser refrigeration.

Development of low-cost photoacoustic imaging systems using very low-energy pulsed laser diodes.

With the growing application of photoacoustic imaging (PAI) in medical fields, there is a need to make them more compact, portable, and affordable. Therefore, we designed very low-cost PAI systems by replacing the expensive and sophisticated laser with a very low-energy laser diode. We implemented photoacoustic (PA) microscopy, both reflection and transmission modes, as well as PA computed tomography systems. The images obtained from tissue-mimicking phantoms and biological samples determine the feasibility of using a very low-energy laser diode in these configurations.

A numerical analysis of a semi-dry coupling configuration in photoacoustic computed tomography for infant brain imaging.

In the application of photoacoustic human infant brain imaging, debubbled ultrasound gel or water is commonly used as a couplant for ultrasonic transducers due to their acoustic properties. The main challenge in using such a couplant is its discomfort for the patient. In this study, we explore the feasibility of a semi-dry coupling configuration to be used in photoacoustic computed tomography (PACT) systems. The coupling system includes an inflatable container consisting of a thin layer of Aqualene with ultrasound gel or water inside of it. Finite element method (FEM) is used for static and dynamic structural analysis of the proposed configuration to be used in PACT for infant brain imaging. The outcome of the analysis is an optimum thickness of Aqualene in order to meet the weight tolerance requirement with the least attenuation and best impedance match to recommend for an experimental setting.

En-face time-domain optical coherence tomography with dynamic focus for high-resolution imaging.

Optical coherence tomography (OCT) is capable of imaging microstructures within translucid samples. A time-domain version of the OCT technology is employed here due to its compatibility with the dynamic focus (DF) procedure. DF means moving the confocal gate in synchronism with the depth scanning via the coherence gate. A DF-OCT setup was implemented for imaging samples at 1300 nm. Its confocal gate of 180 ?? ? m allows the achievement of good and similar transversal resolution along its much larger axial range. Images of a phantom, human skin, teeth, and larynx with and without DF are demonstrated.

Semi-automated localization of dermal epidermal junction in optical coherence tomography images of skin.

Identifying the location of the dermal epidermal junction (DEJ) in skin images is essential in several clinical applications of dermatology such as epidermal thickness determination in healthy versus unhealthy skins, such as basal cell carcinoma. Optical coherence tomography (OCT) facilitates the visual detection of DEJ in vivo. However, due to the granular texture of speckle and a low contrast between dermis and epidermis, a skin border detection method is required for DEJ localization. Current DEJ algorithms work well for skins with a visible differentiable epidermal layer but not for the skins of different body sites. In this paper, we present a semi-automated DEJ localization algorithm based on graph theory for OCT images of skin. The proposed algorithm is performed in an interactive framework by a graphical representation of an attenuation coefficient map through a uniform-cost search method. For border thinning, a fuzzy-based nonlinear smoothing technique is used. For evaluation, the DEJ detection method is used by several experts, and the results are compared with manual segmentation. The mean thickness error between the proposed algorithm and the experts' opinion in the Bland-Altman plot is computed as 14 µm; this is comparable to the resolution of the OCT. The results suggest that the proposed image processing method successfully detects DEJ.

Optimization of excitation of fiber Fabry-Perot tunable filters used in swept lasers using a phase-correction method.

In this paper we investigate a phase-correction method for compensation of the nonlinearity of conventional wavelength-swept laser sources based on a fiber Fabry-Perot tunable filter as a wavelength selective element. A triangular waveform signal is commonly used to drive the filter. We, however, extract the zero crossings from the interferograms and modify the shape of the triangular signal accordingly. This algorithm was tested for different values of the optical path length difference in the interferometer setup. Significant compensation for the nonlinearity of the filter was obtained.

High-resolution wavelet-fractal compressed optical coherence tomography images.

Three-dimensional (3D) optical coherence tomography (OCT) images could assist specialists in the diagnosis of a disease in a tissue by providing morphological information from it. Since the size of such images is usually extremely large, an appropriate image compression method can help in the storage and transmission of these images. Fractal image compression provides very high compression ratios, and discrete wavelet transform (DWT) retains frequency and spatial information in the signal. In order to combine these two techniques, fractal coding has to be performed in the wavelet domain. In this work, we propose a three-dimensional extension version of the wavelet-fractal coding algorithm. The use of 3D fractal approximation to encode 3D wavelet coefficients allows us to exploit inter- and intra-redundancy of the image sequences. The compression results of several OCT images using the 3D wavelet-fractal algorithm are evaluated qualitatively and quantitatively and are compared with the results of the two-dimensional approach. The numerical results illustrate the superior performance of 3D wavelet-fractal algorithm in terms of compression ratio.

The connectivity domain: Analyzing resting state fMRI data using feature-based data-driven and model-based methods.

Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to understand the macro-connectome of the human brain. However, these fluctuations are not synchronized among subjects, which leads to limitations and makes utilization of first-level model-based methods challenging. Considering this limitation of rsfMRI data in the time domain, we propose to transfer the spatiotemporal information of the rsfMRI data to another domain, the connectivity domain, in which each value represents the same effect across subjects. Using a set of seed networks and a connectivity index to calculate the functional connectivity for each seed network, we transform data into the connectivity domain by generating connectivity weights for each subject. Comparison of the two domains using a data-driven method suggests several advantages in analyzing data using data-driven methods in the connectivity domain over the time domain. We also demonstrate the feasibility of applying model-based methods in the connectivity domain, which offers a new pathway for the use of first-level model-based methods on rsfMRI data. The connectivity domain, furthermore, demonstrates a unique opportunity to perform first-level feature-based data-driven and model-based analyses. The connectivity domain can be constructed from any technique that identifies sets of features that are similar across subjects and can greatly help researchers in the study of macro-connectome brain function by enabling us to perform a wide range of model-based and data-driven approaches on rsfMRI data, decreasing susceptibility of analysis techniques to parameters that are not related to brain connectivity information, and evaluating both static and dynamic functional connectivity of the brain from a new perspective.

A Lossless hybrid wavelet-fractal compression for welding radiographic images.

In this work a lossless wavelet-fractal image coder is proposed. The process starts by compressing and decompressing the original image using wavelet transformation and fractal coding algorithm. The decompressed image is removed from the original one to obtain a residual image which is coded by using Huffman algorithm. Simulation results show that with the proposed scheme, we achieve an infinite peak signal to noise ratio (PSNR) with higher compression ratio compared to typical lossless method. Moreover, the use of wavelet transform speeds up the fractal compression algorithm by reducing the size of the domain pool. The compression results of several welding radiographic images using the proposed scheme are evaluated quantitatively and compared with the results of Huffman coding algorithm.

Two applications of solid phantoms in performance assessment of optical coherence tomography systems.

Virtual tissues (phantoms) are widely used for performance evaluation of imaging systems. Specific design of the phantom is necessary for the correct assessment of a system's parameters. In an effort to reduce the amount of time and energy spent making application-oriented phantoms, we describe procedures to make epoxy-resin solid phantoms based on Mie scattering theory, with two different scatterers: polystyrene and gold microspheres. The phantoms are specifically designed to be used in two applications: (a) the gold microspheres solid phantoms are used to estimate the point-spread function (PSF) of an optical coherence tomography (OCT) system, and (b) the polystyrene solid phantom are used to evaluate the performance of an OCT-images optical properties extraction (OPE) algorithm. Phantoms with differing combination of materials have been tested to achieve the most suitable combination for producing an accurate PSF for application (a) and a valid evaluation/parameter optimization of the algorithm in application (b). An en face time-domain dynamic focus OCT is used for imaging.

Speckle reduction using an artificial neural network algorithm.

This paper presents an algorithm for reducing speckle noise from optical coherence tomography (OCT) images using an artificial neural network (ANN) algorithm. The noise is modeled using Rayleigh distribution with a noise parameter, sigma, estimated by the ANN. The input to the ANN is a set of intensity and wavelet features computed from the image to be processed, and the output is an estimated sigma value. This is then used along with a numerical method to solve the inverse Rayleigh function to reduce the noise in the image. The algorithm is tested successfully on OCT images of Drosophila larvae. It is demonstrated that the signal-to-noise ratio and the contrast-to-noise ratio of the processed images are increased by the application of the ANN algorithm in comparison with the respective values of the original images.

Investigation of basal cell carcinoma using dynamic focus optical coherence tomography.

Optical coherence tomography (OCT) is becoming a popular modality for skin tumor diagnosis and assessment of tumor size and margin status. We conducted a number of imaging experiments on periocular basal cell carcinoma (BCC) specimens using an OCT configuration. This configuration employs a dynamic focus (DF) procedure where the coherence gate moves synchronously with the peak of the confocal gate, which ensures better signal strength and preservation of transversal resolution from all depths. A DF-OCT configuration is used to illustrate morphological differences between the BCC and its surrounding healthy skin in OCT images. The OCT images are correlated with the corresponding histology images. To the best of our knowledge, this is the first paper to look at DF-OCT imaging in examining periocular BCC.

Quantitative evaluation of scattering in optical coherence tomography skin images using the extended Huygens-Fresnel theorem.

An optical properties extraction algorithm is developed based on enhanced Huygens-Fresnel light propagation theorem, to extract the scattering coefficient of a specific region in an optical coherence tomography (OCT) image. The aim is to quantitatively analyze the OCT images. The algorithm is evaluated using a set of phantoms with different concentrations of scatterers, designed based on Mie theory. The algorithm is then used to analyze basal cell carcinoma and healthy eyelid tissues, demonstrating distinguishable differences in the scattering coefficient between these tissues. In this study, we have taken advantage of the simplification introduced by the utilization of a dynamic focus OCT system. This eliminates the need to deconvolve the reflectivity profile with the confocal gate profile, as the sensitivity of the OCT system is constant throughout the axial range.

OCT skin image enhancement through attenuation compensation.

The enhancement of optical coherence tomography (OCT) skin images can help dermatologists investigate the morphologic information of the images more effectively. In this paper, we propose an enhancement algorithm with the stages that includes speckle reduction, skin layer detection, and attenuation compensation. A weighted median filter is designed to reduce the level of speckle while preserving the contrast. A novel skin layer detection technique is then applied to outline the main skin layers: stratum corneum, epidermis, and dermis. The skin layer detection algorithm does not make any assumption about the structure of the skin. A model of the light attenuation is then used to estimate the attenuation coefficient of the stratum corneum, epidermis, and dermis layers. The performance of the algorithm has been evaluated qualitatively based on visual evaluation and quantitatively using two no-reference quality metrics: signal-to-noise ratio and contrast-to-noise ratio. The enhancement algorithm is tested on 35 different skin OCT images, which show significant improvements in the quality of the images, especially in the structures at deeper levels.