Search results for: medical image analysis

Authors: Chetsada Noknoi

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The acceptance of Y series refers to the willingness and enjoyment of watching Y series without feeling different from general series. This occurs when people watch Y series and derive happiness and entertainment from it. The viewing experience has the most significant impact on Y series acceptance. This research aims to 1) investigate the levels of acceptance of sexual diversity, image of Y series Actors, media exposure, and Y series acceptance among the residents in three southern border provinces of Thailand, and 2) examine how acceptance of sexual diversity, actor perceptions in Y series, and media exposure influence Y series acceptance in these provinces. The sample consisted of 322 participants from the three southern border provinces of Thailand. The research instrument used was a questionnaire, and data were analyzed using frequency, percentage, mean, standard deviation, and multiple regression analysis. The findings revealed that overall, acceptance of sexual diversity, Image of Y series Actors, and Y series acceptance among the residents in three southern border provinces of Thailand were at a high level, while media exposure was moderate overall. However, the two factors that had the most significant impact on Y series acceptance in these provinces, ranked from highest to lowest influence, were media exposure and acceptance of sexual diversity. Both of these factors had a positive effect on Y series acceptance among the residents in three southern border provinces of Thailand. Collectively, these factors accounted for 40.7% of the variance in Y series acceptance among the residents in three southern border provinces of Thailand.

Keywords: acceptance, acceptance of sexual diversity, image of Y series actors, media exposure, Y series

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Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

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Authors: Anocha Rojanapanich

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This research investigates the effect of financial accounting information and non-financial accounting reports on corporate credibility via strength of board of directors and market environment volatility as moderating effect. Data in this research is collected by questionnaire form non-financial companies listed on the Stock Exchange of Thailand. Multiple regression statistic technique is used for analyzing the data. Results find that firms with greater financial accounting information reports and non-financial accounting information reports will gain greater corporate credibility. Therefore, the corporate reporting has the value for the firms. Moreover, the strength of board of directors will positively moderate the financial and non-financial accounting information reports and corporate credibility relationship. And market environment volatility will negatively moderate the financial and nonfinancial accounting information reports and corporate credibility relationship and the contribution of accounting information reports on corporate credibility is generated to the corporate image. That is the corporate image has affected by corporate credibility.

Keywords: corporate credibility, financial and non-financial reports, firms performance, corporate image

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: Jiangbo Li, Wenqian Huang

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Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

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Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

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Authors: Mariela Gonzalez, Zoraide Lugli, Eleonora Vivas, Rosana Guzmán

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The objective was to determine the predictive capacity of self-efficacy perceived for weight control, locus of weight control and skills of weight self-management in the dissatisfaction of the body image in obese people who attend treatment. Sectional study conducted in the city of Maracay, Venezuela, with 243 obese who attend to treatment, 173 of the feminine gender and 70 of the male, with ages ranging between 18 and 57 years old. The sample body mass index ranged between 29.39 and 44.14. The following instruments were used: The Body Shape Questionnaire (BSQ), the inventory of body weight self-regulation, The Inventory of self-efficacy in the regulation of body weight and the Inventory of the Locus of weight control. Calculating the descriptive statistics and of central tendency, coefficients of correlation and multiple regression; it was found that a low ‘perceived Self-efficacy in the weight control’ and a high ‘Locus of external control’, predict the dissatisfaction with body image in obese who attend treatment. The findings are a first approximation to give an account of the importance of the personal control variables in the study of the psychological grief on the overweight individual.

Keywords: dissatisfaction with body image, obese people, personal control, psychological variables

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Authors: Khairani Binti Supyan, Fatimah Khalid, Mas Rina Mustaffa, Azreen Bin Azman, Amirul Azuani Romle

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Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification.

Keywords: perennial plants, image classification, deep neural networks, fine-tuning, transfer learning, VGG16, ResNet50, InceptionV3

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Authors: Han-Wei Shih, Yao-Nan Wang, Ko-Tung Chang, Lung-Ming Fu

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A multi-channel cell growth real-time monitor and evaluation system using charge-coupled device (CCD) sensors with 40X lens integrating a NI LabVIEW image processing program is proposed and demonstrated. The LED light source control of monitor system is utilizing 8051 microprocessor integrated with NI LabVIEW software. In this study, the same concentration RAW264.7 cells growth rate and morphology in four different culture conditions (DMEM, LPS, G1, G2) were demonstrated. The real-time cells growth image was captured and analyzed by NI Vision Assistant every 10 minutes in the incubator. The image binarization technique was applied for calculating cell doubling time and cell division index. The cells doubling time and cells division index of four group with DMEM, LPS, LPS+G1, LPS+G2 are 12.3 hr,10.8 hr,14.0 hr,15.2 hr and 74.20%, 78.63%, 69.53%, 66.49%. The image magnification of multi-channel CCDs cell real-time monitoring system is about 100X~200X which compares with the traditional microscope.

Keywords: charge-coupled device (CCD), RAW264.7, doubling time, division index

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Authors: Saman Ghaffarian, Ilgin Gökaşar

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This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: aerial images, intelligent transportation systems, traffic density measurement, vehicle detection

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Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

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In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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Authors: R. R. Hordijk, O. J. G. Somsen

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Traditionally, radar systems are the eyes and ears of a ship. However, these systems have their drawbacks and nowadays they are extended with systems that work with video and photos. Processing of data from these videos and photos is however very labour-intensive and efforts are being made to automate this process. A major problem when trying to recognize objects in water is that the 'background' is not homogeneous so that traditional image recognition technics do not work well. Main question is, can a method be developed which automate this recognition process. There are a large number of parameters involved to facilitate the identification of objects on such images. One is varying the resolution. In this research, the resolution of some images has been reduced to the extreme value of 1% of the original to reduce clutter before the polynomial fit (pre-processing). It turned out that the searched object was clearly recognizable as its grey value was well above the average. Another approach is to take two images of the same scene shortly after each other and compare the result. Because the water (waves) fluctuates much faster than an object floating in the water one can expect that the object is the only stable item in the two images. Both these methods (pre-processing and comparing two images of the same scene) delivered useful results. Though it is too early to conclude that with these methods all image problems can be solved they are certainly worthwhile for further research.

Keywords: image processing, image recognition, polynomial fit, water

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Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Rao Muhammad Afzal Khan

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Nano technology is emerging as a useful technology in nearly all areas of Science and Technology. Its role in medical imaging is attracting the researchers towards existing and new imaging modalities and techniques. This presentation gives an overview of the development of the work done throughout the world. Furthermore, it lays an idea into the scope of the future use of this technology for diagnosing different diseases. A comparative analysis has also been discussed with an emphasis to detect diseases, in general, and cancer, in particular.

Keywords: medical imaging, cancer detection, diagnosis, nano-imaging, nanotechnology

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Authors: Yingwei Hou, Tao Liu, Yong Pang

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The paper explored the three-dimensional deformation of mussel plaques anchor to wet polydimethylsiloxane (PDMS) substrates under tension stress with different angles. Mussel plaques exhibiting natural adhesive structures, have attracted significant attention for their remarkable adhesion properties. Understanding their behavior under mechanical stress, particularly in a three-dimensional context, holds immense relevance for biomimetic material design and bio-inspired adhesive development. This study employed a novel approach to investigate the 3D deformation of the PDMS substrates anchored by mussel plaques subjected to controlled tension. Utilizing our customized stereo digital image correlation technique and mechanical mechanics analyses, we found the distributions of the displacement and resultant force on the substrate became concentrated under the plaque. Adhesion and sucking mechanisms were analyzed for the mussel plaque-substrate system under tension until detachment. The experimental findings were compared with a developed model using finite element analysis and the results provide new insights into mussels’ attachment mechanism. This research not only contributes to the fundamental understanding of biological adhesion but also holds promising implications for the design of innovative adhesive materials with applications in fields such as medical adhesives, underwater technologies, and industrial bonding. The comprehensive exploration of mussel plaque behavior in three dimensions is important for advancements in biomimicry and materials science, fostering the development of adhesives that emulate nature's efficiency.

Keywords: adhesion mechanism, mytilus edulis, mussel plaque, stereo digital image correlation

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Authors: Pawan Hinge, Priya Gupta

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Due to cutting edge competitions between organizations and war for talent, the workforce as an asset is gaining significance. The employees are considered as the brand ambassadors of an organization, and their interactions with the clients and customers might impact directly or indirectly on the overall value of the organization. Especially, organizations in the healthcare industry the value of an organization in the perception of their employees can be one of the revenue generating and talent retention strategy. In such context, it is essential to understand that the brand awareness among employees can effect on employer brand image and brand value since the brand ambassadors are the interface between organization and customers and clients. In this exploratory study, we have adopted both quantitative and qualitative approaches for data analysis. Our study shows existing variation among nurses working in different business units of the same organization in terms of their customer interface or interactions and brand awareness.

Keywords: brand awareness, brand image, brand value, customer interface

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Authors: Yongseok Kwon, Woowon Jeong, Eunjin Cho, Sangkug Chung, Kyehan Rhee

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Steady streaming flow fields induced by a 500 um bubble oscillating at 12 kHz were measured using microscopic particle image velocimetry (PIV). The accuracy of velocity measurement using a micro PIV system was checked by comparing the measured velocity fields with the theoretical velocity profiles in fully developed laminar flow. The steady streaming flow velocities were measured in the saggital plane of the bubble attached on the wall. Measured velocity fields showed upward jet flow with two symmetric counter-rotating vortices, and the maximum streaming velocity was about 12 mm/s, which was within the velocity ranges measured by other researchers. The measured streamlines were compared with the analytic solution, and they also showed a reasonable agreement.

Keywords: oscillating bubble, particle image velocimetry, microstreaming, vortices,

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Authors: Didem Venus Yildiz, Murat Hocaoglu, Murat Dursun, Taner Akkan

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The shoulder joint is a more complex structure than the hip or knee joints. In addition to the overall complexity of the shoulder joint, two different factors influence the insufficient outcome of shoulder replacement: the shoulder prosthesis design is far from fully developed and it is difficult to place these shoulder prosthesis due to shoulder anatomy. The glenohumeral joint is the most complex joint of the human shoulder. There are various treatments for shoulder failures such as total shoulder arthroplasty, reverse total shoulder arthroplasty. Due to its reverse design than normal shoulder anatomy, reverse total shoulder arthroplasty has different physiological and biomechanical properties. Post-operative achievement of this arthroplasty is depend on improved design of reverse total shoulder prosthesis. Designation achievement can be increased by several biomechanical and computational analysis. In this study, data of human both shoulders with right side fracture was collected by 3D Computer Tomography (CT) machine in dicom format. This data transferred to 3D medical image processing software (Mimics Materilise, Leuven, Belgium) to reconstruct patient’s left and right shoulders’ bones geometry. Provided 3D geometry model of the fractured shoulder was used to constitute of reverse total shoulder prosthesis by 3-matic software. Finite element (FE) analysis was conducted for comparison of intact shoulder and prosthetic shoulder in terms of stress distribution and displacements. Body weight physiological reaction force of 800 N loads was applied. Resultant values of FE analysis was compared for both shoulders. The analysis of the performance of the reverse shoulder prosthesis could enhance the knowledge of the prosthetic design.

Keywords: reverse shoulder prosthesis, biomechanics, finite element analysis, 3D printing

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Authors: Nadia Ben Youssef, Aicha Bouzid

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Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

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Authors: Okhee Woo

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Purpose: With increasing concern of individual radiation exposure doses, studies analyzing radiation dosage in breast imaging modalities are required. Aim of this study is to compare radiation dosage and image quality between digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM). Methods and Materials: 303 patients (mean age 52.1 years) who studied DBT and FFDM were retrospectively reviewed. Radiation dosage data were obtained by radiation dosage scoring and monitoring program: Radimetrics (Bayer HealthCare, Whippany, NJ). Entrance dose and mean glandular doses in each breast were obtained in both imaging modalities. To compare the image quality of DBT with two-dimensional synthesized mammogram (2DSM) and FFDM, 5-point scoring of lesion clarity was assessed and the better modality between the two was selected. Interobserver performance was compared with kappa values and diagnostic accuracy was compared using McNemar test. The parameters of radiation dosages (entrance dose, mean glandular dose) and image quality were compared between two modalities by using paired t-test and Wilcoxon rank sum test. Results: For entrance dose and mean glandular doses for each breasts, DBT had lower values compared with FFDM (p-value < 0.0001). Diagnostic accuracy did not have statistical difference, but lesion clarity score was higher in DBT with 2DSM and DBT was chosen as a better modality compared with FFDM. Conclusion: DBT showed lower radiation entrance dose and also lower mean glandular doses to both breasts compared with FFDM. Also, DBT with 2DSM had better image quality than FFDM with similar diagnostic accuracy, suggesting that DBT may have a potential to be performed as an alternative to FFDM.

Keywords: radiation dose, DBT, digital mammography, image quality

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Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

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The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

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Authors: M. Y. Lee, S. H. Park, S. M. Yu, H. S. Jo, C. G. Song

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Photoacoustic imaging is the imaging technology that combines the optical imaging with ultrasound. It also provides the high contrast and resolution due to optical and ultrasound imaging, respectively. For these reasons, many studies take experiment in order to apply this method for many diagnoses. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer. In this study, we conduct the experiment using swine and detect the blood of carotid artery and femoral artery. We measured the blood of femoral and carotid artery of swine and reconstructed the image using 950nm due to the HbO₂ absorption coefficient. The photoacoustic image is overlaid with ultrasound image in order to match the position. In blood of artery, major composition of blood is HbO₂. In this result, we can measure the blood of artery.

Keywords: photoacoustic tomography, swine artery, carotid artery, femoral artery

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Tyler D. Cesarone, Tatiana M. Wugalter

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The movement of patients from the Global North to the Global South in pursuit of inexpensive healthcare and touristic experiences dominates the academic discourse on international medical travel (IMT). However, medical travel exists in higher numbers between Global South countries as patients who lack trust in, and feel disenfranchised by, their national healthcare systems seek treatment in nearby countries. Through a review of the existing literature, this paper examines patterns of IMT in the Middle East, Southeast Asia, and Southern Africa, distinguishing North-South medical tourism from South-South intra-regional medical mobility (IRMM). Evidence from these case studies demonstrates that notions of medical distrust and disenfranchisement, rooted in low-resourced and poor quality healthcare systems, are key drivers of IRMM in the Global South. The movement of patients from lower income to proximate higher income countries not only reveals tensions between patients and their healthcare systems but widens gaps in the quality of healthcare between departing and destination countries. In analyzing these cross-regional similarities, the paper moves beyond the current literature’s focus on singular case studies to expose global patterns of South-South IRMM. This presents a shift from the traditional focus on North-South medical tourism, demonstrating how disparities in healthcare systems both influence and are influenced by IRMM.

Keywords: global South, healthcare quality, international medical travel (IMT), intra-regional medical mobility (IRMM), medical disenfranchisement, medical distrust, medical tourism

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Authors: Biljana Marković

Abstract:

Social networks are an integral part of our everyday lives, becoming an indispensable medium for communication in personal and business environments. New forms and ways of communication change the general mindset and significantly affect the quality of life of individuals. Quality of life is perceived as an abstract term, but often people are not aware that they directly affect the quality of their own lives, making minor but significant everyday choices and decisions. Quality of life can be defined broadly, but in the widest sense, it involves a subjective sense of satisfaction with one's life. Scientific knowledge about the impact of social networks on self-assessment of the quality of life of individuals is only just beginning to be researched. Available research indicates potential benefits as well as a number of disadvantages. In the context of the previous claims, the focus of the study conducted by the authors of this paper focuses on analyzing the impact of social networks on individual’s self-assessment of quality of life and the correlation between time spent on social networks, and the choice of content that individuals choose to share to present themselves. Moreover, it is aimed to explain how much and in what ways they critically judge the lives of others online. The research aspires to show the positive as well as negative aspects that social networks, primarily Facebook and Instagram, have on creating a picture of individuals and how they compare themselves with others. The topic of this paper is based on quantitative research conducted on a representative sample. An analysis of the results of the survey conducted online has elaborated a hypothesis which claims that content shared by individuals on social networks influences the image they create about themselves. A comparative analysis of the results obtained with the results of similar research has led to the conclusion about the synergistic influence of social networks on the feeling of the quality of life of respondents. The originality of this work is reflected in the approach of conducting research by examining attitudes about an individual's life satisfaction, the way he or she creates a picture of himself/herself through social networks, the extent to which he/she compares herself/himself with others, and what social media applications he/she uses. At the cognitive level, scientific contributions were made through the development of information concepts on quality of life, and at the methodological level through the development of an original methodology for qualitative alignment of respondents' attitudes using statistical analysis. Furthermore, at the practical level through the application of concepts in assessing the creation of self-image and the image of others through social networks.

Keywords: quality of life, social media, self image, influence of social media

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Authors: Anahit Khananyan

Abstract:

The results of the long-term Jungian analysis with female clients from Eastern and Asian countries, which belong to collectivist cultures, are summarised in the article. The goal of the paper is to describe the cultural complex, which was found by the author in the analysis of women of collectivistic culture. It was named “the repression of Animus”. Generally, C.G.Jung himself and the Post-Jungians studied conditions caused by the possession by Animus. The conditions and cases of the repressed Animus, depending on the type of culture and cultural complexes, as we know, were not widely disseminated. C.G. Jung discovered and recognized the Animus as the second component of a pair of opposites of the psyche of women – femininity and Animus. In the way of individuation, an awareness of manifestations of Animus plays an important role: understanding the differences between negative and positive Animus as well as the Animus and the Shadow, then standing the tension of the presence of a pair of opposites - femininity and Animus, acceptance of the tension of them, finding the balance between them and reconciliation of this opposites. All of the above are steps towards the realization of the Animus, its release Animua, and the healing of the psyche. In the paper, the author will share her experience of analyzing the women of different collectivist cultures and her experience of recognizing the repressed Animus during the analysis. Also, she will describe some peculiarities of upbringing and cultural traditions, which reflected the cultural complex of repression of Animus. This complex is manifested in the traditions of girls' upbringing in accordance with which an image of a woman with overly developed femininity and an absence or underdeveloped Animus is idealized and encouraged as well as an evaluating attitude towards females who have to correspond to this image and fulfill the role prescribed in this way in the family and society.

Keywords: analysis, cultural complex, animus, manifestation, culture

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Authors: Kohei Shimasaki, Tomoaki Okamura, Idaku Ishii

Abstract:

We propose a vibration imaging method for high frame rate (HFR)-video-based localization of vibrating objects with large translations. When the ratio of the translation speed of a target to its vibration frequency is large, obtaining its frequency response in image intensities becomes difficult because one or no waves are observable at the same pixel. Our method can precisely localize moving objects with vibration by virtually translating multiple image sequences for pixel-level short-time Fourier transform to observe multiple waves at the same pixel. The effectiveness of the proposed method is demonstrated by analyzing several HFR videos of flying insects in real scenarios.

Keywords: HFR video analysis, pixel-level vibration source localization, short-time Fourier transform, virtual translation

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Authors: Eli Avraham

Abstract:

The Arab Spring was widely covered in the global media and the number of Western tourists traveling to the area began to fall. The goal of this study was to analyze which media strategies marketers in Middle Eastern countries chose to employ in their attempts to repair the negative image of the area in the wake of the Arab Spring. Several studies were published concerning image-restoration strategies of destinations during crises around the globe; however, these strategies were not part of an overarching theory, conceptual framework or model from the fields of crisis communication and image repair. The conceptual framework used in the current study was the ‘multi-step model for altering place image’, which offers three types of strategies: source, message and audience. Three research questions were used: 1.What public relations crisis techniques and advertising campaign components were used? 2. What media policies and relationships with the international media were adopted by Arab officials? 3. Which marketing initiatives (such as cultural and sports events) were promoted? This study is based on qualitative content analysis of four types of data: 1) advertising components (slogans, visuals and text); (2) press interviews with Middle Eastern officials and marketers; (3) official media policy adopted by government decision-maker (e.g. boycotting or arresting newspeople); and (4) marketing initiatives (e.g. organizing heritage festivals and cultural events). The data was located in three channels from December 2010, when the events started, to September 31, 2013: (1) Internet and video-sharing websites: YouTube and Middle Eastern countries' national tourism board websites; (2) News reports from two international media outlets, The New York Times and Ha’aretz; these are considered quality newspapers that focus on foreign news and tend to criticize institutions; (3) Global tourism news websites: eTurbo news and ‘Cities and countries branding’. Using the ‘multi-step model for altering place image,’ the analysis reveals that Middle Eastern marketers and officials used three kinds of strategies to repair their countries' negative image: 1. Source (cooperation and media relations; complying, threatening and blocking the media; and finding alternatives to the traditional media) 2. Message (ignoring, limiting, narrowing or reducing the scale of the crisis; acknowledging the negative effect of an event’s coverage and assuring a better future; promotion of multiple facets, exhibitions and softening the ‘hard’ image; hosting spotlight sporting and cultural events; spinning liabilities into assets; geographic dissociation from the Middle East region; ridicule the existing stereotype) and 3. Audience (changing the target audience by addressing others; emphasizing similarities and relevance to specific target audience). It appears that dealing with their image problems will continue to be a challenge for officials and marketers of Middle Eastern countries until the region stabilizes and its regional conflicts are resolved.

Keywords: Arab spring, cultural events, image repair, Middle East, tourism marketing

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