The objective of the present study is to verify the actual carious lesion depth by laser
fluorescence technique using 650 nm CW diode laser in comparison with the histopathological
investigation. Five permanent molar teeth were extracted from adult individuals for different reasons
(tooth impaction, periodontal diseases, and pulp infections); their ages were ranging from 20-25 years
old. Different carious teeth with varying clinical stages of caries progression were examined. An
experimental laser fluorescence set-up was built to perform the work regarding in vitro detection and
quantification of occlusal dental caries and the determination of its actual clinical carious lesion depth by
650 nm CW diode laser (excitation wavelength (λexcit.) = 669 nm). Five teeth were sent to
histopathological examination to confirm the efficacy of laser fluorescence technique for the
determination of actual carious lesion depth. The results are leading to the detection of carious lesions for
different depths. The deepest carious lesions revealed high fluorescence intensity. Based on these
findings; it was concluded that 650 nm CW diode laser (λexcit. = 669 nm 40 mW) is a suitable and a
reliable tool for caries diagnosis and depth assessment. Histopathological findings for the estimation of
actual carious lesion depth revealed a good correlation with that of laser fluorescence technique.
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A new technique for embedding image data into another BMP image data is presented. The image data to be embedded is referred to as signature image, while the image into which the signature image is embedded is referred as host image. The host and the signature images are first partitioned into 8x8 blocks, discrete cosine transformed “DCT”, only significant coefficients are retained, the retained coefficients then inserted in the transformed block in a forward and backward zigzag scan direction. The result then inversely transformed and presented as a BMP image file. The peak signal-to-noise ratio (PSNR) is exploited to evaluate the objective visual quality of the host image compared with the original image.
CO2 laser (10.6 μm) is the most often used laser in the oral surgery due to its high absorption by water of the oral tissues. Several benefits of the use of CO2 laser have been reported for oral surgical procedures. This study aims to evaluate the effect of CO2 laser on soft and hard oral tissues (in vitro study). This study was done on fresh tissues from sheep’s head. CO2Surgical Laser with different operation modes was used; 0.2 mm spot size using different laser parameters on the tongue, and bone making holes, incisions and cutting. The depths and widths of holes and incisions were measured using endodontic file under magnification. The speed of incisions was calculated and the required time for cutting was measured using sport clo
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The prepared nanostructure SiO2 thin films were densified by two techniques (conventional and Diode Pumped Solid State Laser (DPSS) (532 nm). X-ray diffraction (XRD), Field Emission Scanning electron microscopy (FESEM), and Atomic Force Microscope (AFM) technique were used to analyze the samples. XRD results showed that the structure of SiO2 thin films was amorphous for both Oven and Laser densification. FESEM and AFM images revealed that the shape of nano silica is spherical and the particle size is in nano range. The small particle size of SiO2 thin film densified by DPSS Laser was (26 nm) , while the smallest particle size of SiO2 thin film densified by Oven was (111 nm).
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A theoretical model is developed to determine time evolution of temperature at the surface of an opaque target placed in air for cases characterized by the formation of laser supported absorption waves (LSAW) plasmas. The model takes into account both plasma dynamics and time variation of incident laser pulse (i.e. pulse shape or profile).Shock tube relations were employed in formulating plasma dynamics over target surface. Gaussian function was chosen in formulating the pulse profile in the present modeling
In this study, an unknown force function dependent on the space in the wave equation is investigated. Numerically wave equation splitting in two parts, part one using the finite-difference method (FDM). Part two using separating variables method. This is the continuation and changing technique for solving inverse problem part in (1,2). Instead, the boundary element method (BEM) in (1,2), the finite-difference method (FDM) has applied. Boundary data are in the role of overdetermination data. The second part of the problem is inverse and ill-posed, since small errors in the extra boundary data cause errors in the force solution. Zeroth order of Tikhonov regularization, and several parameters of regularization are employed to decrease error
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
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