In this paper, an alternative approach in operational modal analysis is presented, utilizing image processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

Background: Identification and precise localization of the liver surface and its segments are essential for any surgical treatment. An algorithm of accurate liver segmentation simplifies the treatment planning for different types of liver diseases. Although liver segmentation turns researcher’ s attention, it still has some challenging problems in Computer-aided diagnosis. Objective: This study aimed to extract the potential liver regions by an adaptive water flow model and perform the final segmentation by the classification algorithm. Material and Methods: In this experimental study, an automatic liver segmentation algorithm was introduced. The proposed method designed the image by a transfer function based on the probability distribution function of the liver pixels to enhance the liver area. The enhanced image is then segmented using an adaptive water flow model in which the rainfall process is controlled by the liver location in the training images and the gray levels of pixels. The candidate liver segments are classified by a Multi-Layer Perception (MLP) neural network considering some texture, area, and gray level features. Results: The proposed algorithm efficiently distinguishes the liver region from its surrounding organs, resulting in perfect liver segmentation over 250 Magnetic Resonance Imaging (MRI) test images. The accuracy of 97% was obtained by quantitative evaluation over test images, which revealed the superiority of the proposed algorithm compared to some evaluated algorithms. Conclusion: Liver segmentation using an adaptive water flow algorithm and classifying the segmented area in MRI images yields more robust and reliable results in comparison with the classification of pixels.

Background: Smile esthetics can be subjective. This study aims to assess the effect of culture/ geographic location on judging smile esthetics by comparing the perception of smile characteristics between American laypersons (Western culture) and Iranians (Eastern). Materials and Methods: One hundred residents from each country were recruited for this analytical cross‑sectional study. A frontal picture of a posed smile with standard norms which are mentioned in the Contemporary Orthodontics textbook by William R. Proffit was selected. Adobe Photoshop 7 was used to alter midline diastema, gingival display (GD), maxillary midline‑to‑face discrepancy, buccal corridor (BC), and smile arc. images were given to groups to determine the most attractive and acceptable smile. Data were analyzed by Chi‑square, Mann–Whitney, and Spearman correlation coefficient in SPSS‑22 (α =0. 05). Results: Americans were less critical in judging diastema (P < 0. 001), GD (P = 0. 013), and BC (P = 0. 004) for smile attractiveness than Iranians. No difference was between the two groups in choosing the acceptability threshold and determining the most attractive smile except for BC (P = 0. 002). Conclusion: Overall, Americans were more tolerant of variations in smile characteristics than Iranians. Both groups agreed on most smiles. Therefore, it seems that it is reasonable to use similar standards for smile characteristics while considering the small differences

Background: One of the spine deformities is scoliosis, and Cobb angle is generally used to assess it. Objectives: In this study, a Computer-aided measurement system (CAMS) was presented as a new repeatable and reproducible approach to assess the Cobb angle in idiopathic scoliosis patients. Methods: Python libraries, including OpenCV and Numpy were used for image processing and design of the software. To assess the repeatability and reproducibility of the CAMS, a series of 98 anterior-posterior radiographs from patients with idiopathic scoliosis were used. Assessments were done by five independent observers. Each radiograph was assessed by each observer three times with a minimum break of two weeks among assessment. The single measure intraclass correlation coefficient (ICC), the mean absolute difference (MAD), and the standard error measurement (SEM) values were used for intra-and inter-observer reliability. Results: The inter-observer analysis indicated that the ICCs ranged from 0. 94-0. 99, and the MAD between manual and CAMS were less than 3°, . For intra-observer measurements, the combined SEM between all observers for the manual and CAMS was 1. 79°,and 1. 27°, , respectively. An ICC value of 0. 97 with 95% confi, dence interval (CI) was excellent in CAMS for inter-observer reliability. The MAD of CAMS was 2. 18 ,2. 01 degrees. Conclusions: The CAMS is an effective and reliable approach for assessing scoliotic curvature in the standing radiographs of thoraco-lumbar. Moreover, CAMS can accelerate clinical visits, and its calculation results are reliable.

Knowledge on sunflower seed physical characteristics can play an important role in the proper procedures during harvesting, transport, drying, sorting, seed peeling and storage. In order to study the effect of removing leaf and seed in different plant densities on seed physical and chemical properties of sunflower hybrids, an experiment was conducted as a factorial split plot based on completely randomized block design with three replications in 2009 at Aboureihan Research Field of University of Tehran. Azargol and new Iranian hybrid SHF81-90 and three plant densities 60000, 80000 and 100000 plants/ha were main plots and five levels of change in source and sink size (removed 50% lower leaves, removed 50% upper leaves, removed 50% seeds, removed 25% seeds) and control (without removing leaf and seed) were sub plots. Photographs were taken from the seeds, by a digital camera, and analyzed using MATLAB programming language. Some morphological features were extracted by this software. Results indicated that the hybrids had significant difference in Perimeter and Area, Major and Minor Axis, Elongation, Compactness, Roundness, Solidity, seed weight and seed coat to seed ratio at 5% and 1% probability levels. Also the effects of plant density and source and sink manipulation were significant on all traits. Oil percent increased along with the plant density increase. Correlation between oil percent with seed weight (r=+0.53) and seed coat to seed ratio (r=-0.27) was significant at 1% probability level. Also the results of this study showed that using image processing technique, which is the new technique in agricultural researches, the physical properties of seed cultivars in different environmental conditions can be identified more accurately and this will be helpful in management of different planting, harvesting and postharvest stages.

Objectives The aim of this study was to evaluate the validity and reliability of a newly designed cephalometric analysis program (Hexagon software) in comparison with manual and digital (Dolphin software) tracings. Methods Pre-treatment lateral cephalometric radiographs of 32 adult patients between 18 to 41 years (10 males and 22 females, mean age of 22. 78 ± 5. 17 years) were randomly chosen. For each radiograph, 10 angular and 6 linear measurements were calculated using three different methods (manual and digital using two different software programs). The cephalograms were manually traced using acetate paper, x-ray light box, 0. 3 mm HB pencil, ruler, and protractor. For digital tracing, cephalograms were traced with Dolphin vertion-10 (USA) and Hexagon (Iran) software programs. All the analyses were performed by one operator 2 times with at least a four-week interval between the two tracings. The intra-class correlation coefficient (ICC) was used to evaluate the intra-examiner agreement, while the differences between the methods were analyzed using paired t-test, and ANOVA. Results The intra-examiner repeatability of all measurements in all three tracing methods showed high agreement. Differences in measurements between the two software programs and hand tracing were not statistically significant for any of the cephalometric parameters (P>0. 05). Conclusion The results demonstrated that the accuracy of cephalometric tracing by the Hexagon software was similar to the Dolphin software, and the manual tracing technique.

Objectives: The purpose of this study was to develop and test a new tool for radiographic densitometry by combining periapical films and aluminum step wedge.Materials and Methods: We reviewed 50 Kodak E-speed intraoral films. An aluminum step wedge consisting of 16 steps was constructed. Each step was 1mmx3mx10mm. The step wedge was exposed to varying exposure times, ranging from 0.05 second to 0.5 second, increasing in 0.05 second increments. Films were digitalized after processing and the MATLAB software algorithm was ran subsequently. Density of the films was measured again using a digital densitometer. In order to compare the two imaging techniques, three steps were selected. Output data from the MATLAB algorithm were compared with data obtained from the digital densitometer.Results: The new method could detect significant differences between subsequent exposure times in step 7, while the densitometer did that in steps 7 and 12. The new method’s sensitivity in determining density changes was 5.26%, 84.1% and 93.02% in steps 2, 7, and 12 respectively.Conclusions: Our new method has an acceptable sensitivity for determining density changes of at least 7 mmEq/Al.

Background: To investigate the success rate and quality of automatic airway segmentation using ultra-low dose CT (ULD-CT) images of different reconstruction algorithms. Materials and Methods: Fifty two children who underwent chest ULD-CT were divided into three groups for analysis based on age: group A (n=13, age, 1-2years), group B (n=19, age, 3-6years) and group C (n=20, age, 7-13years). CT images were reconstructed with filtered back-projection (FBP), 50% adaptive statistical iterative reconstruction-Veo (50%ASIR-V), 100%ASIR-V, deep learning image reconstruction (DLIR) with low (DLIR-L), medium (DLIR-M), and high (DLIR-H) strengths. Subjective image quality was evaluated using a 5-point scale. CT value, noise, and sharpness of the trachea were measured. The VCAR software was used to automatically segment airways and reported the total volume. Segmentation success rates were recorded, and segmentation images were subjectively evaluated using a 6-point scale. Results: The average tracheal diameters were 8. 53±1. 88mm, 10. 69±1. 65mm, and 12. 72±1. 97mm, respectively for groups A, B, and C. The segmentation success rate depended on patient groups: group C reached 100%, while group A decreased significantly. In group A, 100%ASIR-V had the lowest rate at 7. 69%, while DLIR-M and DLIR-H significantly improved the rate to 38. 64% (P=0. 03). For the segmented images, DLIR-H provided the lowest noise and highest subjective score while FBP images had the highest noise and 100%ASIR-V had the lowest overall score (P<0. 05). There was no significant difference in the total airway volume among the six reconstructions. Conclusion: The airway segmentation success rate in ULD-CT for children depends on the tracheal size. DLIR improves airway segmentation success rate and image quality.