Speckle Reduction with Attenuation Compensation for Skin OCT Images Enhancement

The enhancement of skin image in optical coherence tomography (OCT) imaging can help dermatologists to investigate tissue layers more accurately, hence the more efficient diagnosis. In this paper, we propose an image enhancement technique including speckle reduction, attenuation compensation and cleaning to improve the quality of OCT skin images. A weighted median filter is designed to reduce the level of speckle noise while preserving the contrast. A novel border detection technique is designed to outline the main skin layers, stratum corneum, epidermis and dermis. A model of the light attenuation is then used to estimate the absorption coefficient of epidermis and dermis layers and compensate the brightness of the structures at deeper levels. The undesired part of the image is removed using a simple cleaning algorithm. The performance of the algorithm has been evaluated visually and numerically using the commonly used no-reference quality metrics. The results shows an improvement in the quality of the images. Keywords: Optical coherence tomography (OCT), Skin, Image enhancement, Speckle reduction, Attenuation compensation

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

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

High resolution functional photoacoustic computed tomography of the mouse brain during electrical stimulation

Photoacoustic computed tomography (PACT) is an emerging imaging technique which is based on the acoustic detection of optical absorption from tissue chromophores, such as oxy-hemoglobin and deoxy-hemoglobin. An important application of PACT is functional brain imaging of small animals. The conversion of light to acoustic waves allows PACT to provide high resolution images of cortical vasculatures through the intact scalp. Here, PACT was utilized to study the activated areas of the mouse brain during forepaw and hindpaw stimulations. Temporal PACT images were acquired enabling computation of hemodynamic changes during stimulation. The stimulations were performed by trains of pulses at different stimulation currents (between 0.1 to 2 mA) and pulse repetition rates (between 0.05 Hz to 0.01Hz). The response at somatosensory cortex-forelimb, and somatosensory cortex-hindlimb, were investigated. The Paxinos mouse brain atlas was used to confirm the activated regions. The study shows that PACT is a promising new technology that can be used to study brain functionality with high spatial resolution

Imaging technology in mice enhances human brain research

Photoacoustic tomography offering a large field of view and high spatial resolution enables, for the first time, noninvasive imaging of resting-state functional connectivity in the murine brain

Imaging technology in mice enhances human brain research

Photoacoustic tomography offering a large field of view and high spatial resolution enables, for the first time, noninvasive imaging of resting-state functional connectivity in the murine brain

Wavefront aberration correction in single mode fibre systems

A simple control loop system was built for the purpose of optimized compensation of wavefront aberrations correction using a micromachined deformable mirror controlled by PCI cards and sound card through simulated annealing algorithm implemented by using the integration of Visual C++ and MATLAB in MATLAB environment

Investigation of computer-based skin cancer detection using optical coherence tomography

In this paper, a procedure for computer-based detection of skin cancer, and in particular basal cell carcinoma (BCC), to assist dermatologists is investigated. The tissue compartments, which discriminate healthy and cancerous skins from an optical properties point of view, are studied. The application of an image-processing algorithm on a three-dimensional (3D) optical coherence tomography (OCT) image is explained. The algorithm finds the differences between healthy skin and BCC lesion by extracting scattering coefficient ?s, absorption coefficient ?a, and anisotropy factor g, from the 3D image of skin. We present the essential stages required to design a computer-based skin cancer detection algorithm using OCT and evaluate the performance of the algorithm using a phantom. The procedure to design the phantom and the choice of material used to model skin tissue based on BCC discriminators are discussed in detail

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

Denoising Based on Noise Parameter Estimation in Speckled OCT Images Using Neural Network

This paper presents a neural network based technique to denoise speckled images in optical coherence tomography (OCT). Speckle noise is modeled as Rayleigh distribution, and the neural network estimates the noise parameter, sigma. Twenty features from each image are used as input for training the neural network, and the sigma value is the single output of the network. The certainty of the trained network was more than 91 percent. The promising image results were assessed with three No-Reference metrics, with the Signal-to-Noise ratio of the denoised image being considerably increased