We propose an algorithm to compensate for the refractive index error in the optical coherence tomography (OCT) images of multilayer tissues, such as skin. The performance of the proposed method has been evaluated on one- and two-layer solid phantoms, as well as the skin of rat paw.
There is a need for continued research into the diagnosis, prevention and cure of neonatal brain disease and disorders. These disorders lead to fatalities and developmental disorders in infants. Non-invasive imaging techniques are being researched for this purpose. However, the availability of neonatal skull samples for this work is very low. A phantom can be used to simulate the neonatal skull and brain to improve imaging techniques. This study selects a phantom of polyurethane and titanium dioxide and proves its value as a replacement for neonatal skull in research. The methods used for this proof are validation of choice against the literature, transmissivity and acoustic experimentation compared to existing literature, and finally photoacoustic evaluation of the final choice to show its usefulness as a neonatal skull phantom.
Photoacoustic imaging (PAI) has proved to be a promising non-invasive technique for diagnosis, prognosis and treatment monitoring of neurological disorders in small and large animals. Skull bone effects both light illumination and ultrasound propagation. Hence, the PA signal is largely affected. This study aims to quantify and compare the attenuation of PA signal due to the skull obstacle in the light illumination path, in the ultrasound propagation path, or in both. The effect of mouse, rat, and mesocephalic dog skull bones, ex-vivo, is quantitatively studied.
Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.
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