Background and Objective: One of the most common extracutaneous complications in psoriasis patients is ocular complications, which is controversial concerning its effect on choroidal thickness. This study aimed to compare the psoriasis patients with healthy individuals in terms of the thickness of the choroidal layer using the Optical coherence tomography technique. Materials and Methods: In this case-control study, 30 psoriasis patients were compared with 32 healthy individuals who were matched for gender and age. Choroidal thickness was measured in both groups using the Optical coherence tomography technique. Furthermore, the relationship of the choroidal thickness with the severity and duration of the disease was assessed in patients. Results: The mean choroidal thickness of the left eye (312. 1± 12. 0 mμ vs. 296. 3± 20. 8 mμ ), right eye (310. 6± 12. 5mμ vs. 297. 5± 17. 5mμ ), and regardless of the left or right eye (311. 3± 12. 2 mμ vs. 296. 9± 19. 1mμ ) was significantly higher in patients, compared to the control group (P=0. 001 for all three mean values). No significant relationship was found between disease duration and severity with choroid thickness. Moreover, the patients with multiple limb involvement had a higher mean choroid thickness; however, it was not statistically significant. Conclusion: According to the results of the present study, patients with psoriasis have a greater choroidal thickness, compared to healthy individuals, which is not related to the severity, type of involvement, and duration of the disease.

Background: The symmetricity of even organs of body may help clinicians in the early detection of diseases.So, we estimated the cup-to-disk ratio (CDR) in left and right eyes and checked the symmetricity between the two eyes using the data of Optical coherence tomography (OCT).Methods: In this study, data from 40 normal subjects were used. This data was taken from the 3D-OCT1000 Tapcon model. For estimating CDR in each B-scan, at first the internal limiting membrane (ILM) and retinal pigment epithelium (RPE) layers were extracted; then using the end-point of RPE layer and the depth of cup, the boundary of disk and cup were determined. Finally, CDR of each B-scan was compared point-by-point and the symmetricity parameters were evaluated.Findings: CDRs in the left and right eyes of 40 normal data were investigated locally. We divided optic disk area into three regions named upper, middle and lower. Then, CDR of each region was calculated for left and right eyes of each patient. The local CDR were 0.433±0.0548, 0.432±0.061, and 0.432±0.0635 for the right eyes and 0.441±0.0635, 0.443±0.0731, and 0.417 ± 0.675 for the left eyes in upper, middle and lower regions, respectively. The differences between local CDRs in different regions of the two eyes were 0.0483±0.042, 0.0420±0.039, and 0.067±0.045, respectively.Conclusion: The results of local comparison of CDRs between the left and right eyes indicated that the level of asymmetricity in the lower region of disk was higher than upper and middle regions, and the middle region has the most symmetricity. In addition, in point-by-point symmetricity evaluation of CDRs, the highest level of symmetricity is seen in the second B-scan, near the center of optic disk.

In recent years, Optical neural networks have received a lot of attention due to their high speed and low power consumption. However, these networks still have many limitations. One of these limitations is implementing their nonlinear layer. In this paper, the implementation of nonlinear unit for an Optical convolutional neural network is investigated, so that using this nonlinear unit, we can realize an all-Optical convolutional neural network with the same accuracy as the electrical networks, while providing higher speed and lower power consumption. In this regard, first of all, different methods of implementing Optical nonlinear unit are reviewed. Then, the impact of utilizing saturable absorber, as the nonlinear unit in different layers of CNN, on the network’, s accuracy is investigated, and finally, a new and simple method is proposed to preserve the accuracy of the Optical neural networks utilizing saturable absorber as the nonlinear activating function.

In this paper, stray lights in Optical system of remote sensing satellite camera is simulated. For this purpose, stray lights, sources of production and their destructive effects on the image quality is studied. Moreover, mechanisms to deal with these unwanted lights are presented. Then, the effect of Optical housing and surface coatings on the performance of stray light in satellite camera, has been studied by the results of the simulation. Finally an optimal design includes a set of different techniques for improving the performance of the considered camera was selected. Simulation results show that by this method, at large angles, stray lights can be completely eliminated whereas at angles near the FOV, stray lights intensities can be very much reduced namely up to 100000 times of their original intensity without almost no serious disturbance in the camera’s field of view.

Background: Retina is the innermost tissue in human eye which sends visual information to the brain by means of optic nerve. Designing an intra-retinal layer segmentation method which can detect the retina surfaces properly in the presence of noise and lack of contrast is an important step in ophthalmology. In this study the combination of morphological component analysis (MCA) and dynamic programming (DP) is used automatically for segmentation of Optical coherence tomography (OCT) images.Methods: Data set for this study was 55 samples which were taken from normal people by Topcon OCT-1000.This study had two phases. In MCA phase the image dictionary was created by clustering with eigenvalues (k-SVD), and then the image was decomposed to cartoon and texture parts by selecting proper bases. In the second phase segmentation was done by the dynamic programming (DP) method on cartoon part and the retinal pigment epithelium (RPE), Verhoeff's memberane (VM), outer segment layer (OSL), innercollagenous layer (ICL), inner synaptic layer (ISL), and outer limiting membrane (OLM) layers were detected.Findings: Comparing the obtained results with gold standard (manual segmentation) shows that minimum error belongs to OSL surface and its error in the form of mean±SD (standard derivation) is 0.030±0.167. For other surfaces the error is calculated in this way from left to right for RPE, VM, ICL, ISL, OLM: -0.66±0.33, -0.59±0.31, -1.00±0.49, -1.72±0.61, -1.05±0.51.Conclusion: MCA in combination with DP can work as an automatic method for six lower intra retina layers' segmentation with acceptable accuracy. One of the main advantages of this method is omitting preprocessing phase for segmentation.

This paper demonstrates the design of an Arrayed Waveguide Gratings (AWG) based Optical switch. In the design both physical and network layer analysis is performed. The physical layer power and noise analysis is done to obtain Bit Error Rate (BER). This has been found that at the higher bit rates, BER is not affected with number of buffer modules. Network layer analysis is done to obtain performance in terms of packet loss rate and average delay. Analysis presented in the paper clearly reveals that there is a minimum amount of power required, which is necessary for the satisfactory performance of switch both at physical and network layer.