Search results for: mental images

Authors: Katja Siefken, Astrid Junge

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Background: Research indicates that physical activity (PA) protects us from developing mental disorders. The knowledge regarding optimal domain, intensity, type, context, and amount of PA promotion for the prevention of mental disorders is sparse and incoherent. The objective of this study is to determine the relationship between PA domains and mental well-being, and whether associations vary by domain, amount, context, intensity, and type of PA. Methods: 310 individuals (age: 25 yrs., SD 7; 73% female) completed a questionnaire on personal patterns of their PA behaviour (IPQA) and their mental health (Centre of Epidemiologic Studies Depression Scale (CES-D), Generalized Anxiety Disorder (GAD-7) scale, the subjective physical well-being (FEW-16)). Linear and multiple regression were used for analysis. Findings: Individuals who met the PA recommendation (N=269) reported higher scores on subjective physical well-being than those who did not meet the PA recommendations (N=41). Whilst vigorous intensity PA predicts subjective well-being (β = .122, p = .028), it also correlates with depression. The more vigorously physically active a person is, the higher the depression score (β = .127, p = .026). The strongest impact of PA on mental well-being can be seen in the transport domain. A positive linear correlation on subjective physical well-being (β =.175, p = .002), and a negative linear correlation for anxiety (β =-.142, p = .011) and depression (β = -.164, p = .004) was found. Multiple regression analysis indicates similar results: Time spent in active transport on the bicycle significantly lowers anxiety and depression scores and enhances subjective physical well-being. The more time a participant spends using the bicycle for transport, the lower the depression (β = -.143, p = .013) and anxiety scores (β = -.111,p = .050). Conclusions: Meeting the PA recommendations enhances subjective physical well-being. Active transport has a substantial impact on mental well-being. Findings have implications for policymakers, employers, public health experts and civil society. A stronger focus on the promotion and protection of health through active transport is recommended. Inter-sectoral exchange, outside the health sector, is required. Health systems must engage other sectors in adopting policies that maximize possible health gains.

Keywords: active transport, mental well-being, health promotion, psychological disorders

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Authors: Han Hongmei

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University image is receiving attention because of its key role in influencing student choice, faculty loyalty, and social recognition. Therefore, all universities strive to promote their positive images. However, for most people, the positive image of a university is often from fragmented perceptual understanding. Since universities’ official websites are important channels for image promotion, a corpus approach to university profiles in their official websites can reveal holistic positive images of universities. This study aims to compare positive images of high-level universities in China and English-speaking countries based on a profile corpus of theseuniversities. It is found that the positive images revealed in these university profiles are similar, with some minor differences. The similarities are reflected in the campus environment, historical achievements, comprehensive characteristics, scientific research institutions, and diversified faculty; while the differences are reflected in their unique characteristics. Furthermore, the findings also reveal a gap between Chinese universities and high-level universities in the English-speaking countries.

Keywords: university image, positive image, corpus of university profiles, comparative analysis, high-frequency words

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Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

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Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

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Authors: Anam Naveed, Asma Andleeb, Mehreen Sirshar

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In the article, Image processing techniques have been applied on cardiac images for enhancing the image quality. Two types of methodologies considers for survey, invasive techniques and non-invasive techniques. Different image processes for improvement of cardiac image quality and reduce the amount of radiation exposure for invasive techniques are explored. Different image processing algorithms for enhancing the noninvasive cardiac image qualities are described. Beside these two methodologies, third methodology has applied on live streaming of heart rate on ECG window for extracting necessary information, removing noise and enhancing quality. Sensitivity analyses have been carried out to investigate the impacts of cardiac images for diagnosis of cardiac arteries disease and how the enhancement on images will help the cardiologist to diagnoses disease. The paper evaluates strengths and weaknesses of different techniques applied for improved the image quality and draw a conclusion. Some specific limitations must be considered for whole survey, like the patient heart beat must be 70-75 beats/minute while doing the angiography, similarly patient weight and exposure radiation amount has some limitation.

Keywords: cardiac images, CT angiography, critical analysis, exposure radiation, invasive techniques, invasive techniques, non-invasive techniques

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Authors: Amina Salem Attia

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This east project consists in studying The child's mental health is the medium through which he expresses his thoughts, so pay attention to it because it is an essential building block in the process of building the child's future personality, where it gives him a balance between feelings and mental thoughts, and since the family is the child's first guardian, it greatly affects his personality and psychological development. As the disturbed environment contributes to behavioral deviations and mental disorders, unlike the stable environment, which plays a major role in developing the child's abilities and forming his psychologically sound attitudes, this should not be forgotten about the role of the school, it is also the second social institution after the family and has a major impact on the child's mental health as it contributes It is important in forming the child's personality and developing his skills and achieving his healthy psychological development, by providing him with psychological care and helping him to solve his problems by using models that are valid for the behavior that is taught to him or that the teachers present in their daily behavior with him.

Keywords: psychological, behavioral problems, children, school education

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Authors: Sumaiyya Ali, Humaira Jamshed

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Selfie culture has become increasingly prevalent in recent years, with young adults being one of the most active demographics when it comes to taking and sharing selfies. While some argue that selfies can be a harmless way to express oneself, connect with others, and boost self-esteem, others have raised concerns about the potential negative effects of selfie culture on mental health. This study investigated the complex relationship between selfie culture, social media use, self-image, and mental well-being among young adults. A cross-sectional survey was conducted with over 75 participants aged 18–30. The results of the study showed that there is a positive relationship between selfie culture and social media use and that both of these factors are associated with lower self-esteem, higher self-consciousness, and increased appearance anxiety among young adults. Additionally, the study found that selfie culture was associated with increased narcissistic traits among young adults. The findings of this study suggest that selfie culture may have some negative effects on the mental health of young adults. However, it is important to note that the study was cross-sectional, which means that it cannot establish causality. Future research is needed to further investigate the relationship between selfie culture and mental health. In addition to the findings of the study, it is also important to consider the motivation behind selfie-taking. The study identified four main motivations for taking selfies: to communicate with others, to promote oneself, to express oneself, and to seek attention. It is likely that the negative effects of selfie culture are more pronounced for individuals who take selfies for narcissistic or attention-seeking reasons. Overall, the findings of this study suggest that selfie culture is a complex phenomenon with both positive and negative potential effects on the mental health of young adults. It is important to be aware of the potential risks associated with selfie culture, and to use it in a healthy and balanced way.

Keywords: selfie, social media, psychology, mental health

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Snehal G. Teli, R. J. Shelke

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CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

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Authors: Zolani Metu

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The death of more than 140 psychiatric patients who were unethically deinstitutionalized from the Life Esidimeni hospital Johannesburg, in 2016, shined a light on South Africa’s failing public mental healthcare system. Compounded by insufficient research evidence on African deinstitutionalization, this necessitates inquiries into deinstitutionalized mental healthcare, reintegration and community-based mental healthcare within the South African context. This study employed a quantitative research approach which utilized a cross-sectional research design, to investigate experiences with the reintegration of institutionalized forensic mental health service users into communities in the Western Cape, South Africa. A convenience sample of 100 mental health care workers from different occupational and organizational backgrounds in the Western Cape was purposively selected using the Western Cape Health Directorate as a sampling frame. A self-administered questionnaire (SAQ) was used as the data collection instrument. The results of the study indicate that criminogenic factors such as substance use, history of violent behaviour, criminal history and disruptive social behaviour complicate the reintegration of forensic mental health service users into communities. The current extent of reintegration of forensic mental health service users was found to be 'poor' (46%; n= 46); and financial difficulties, criminogenic factors and limited Community-Based Care (CBC) facilities were identified as key barriers to the reintegration process. 56% of all job applications for forensic mental health service users were unsuccessful, and 53% of all applications for their admission into CBC facilities were declined. Although social support (informal) was found to be essential for successful reintegration, institutional support (formal) through assertive community treatment (35%; n= 35) and CBC facilities (21%) and the disability grant (DG=50%) was found to be more important for family coping and reintegration. Moreover, 72% of respondents had positive perceptions about the process of reintegration; no statistically significant relationship was found between years of experience and perceptions about reintegration (P-value = 0.062); and perceptions were not found to be a barrier to reintegration. No statistically significant relationship was found between years of working experience and understanding the legislative framework of deinstitutionalization (P-Value =.0.061). However, using a Chi-square test, a significant relationship (P-value = 0.021) was found between sex and understanding the legal framework involved in the process of reintegration. The study recommends a post-2020 deinstitutionalization agenda that factors-in criminogenic realities associated with forensic mental health service users, and affirms the strengthening of PHC and community based care systems as precedents of successful deinstitutionalization and reintegration of mental health service users.

Keywords: forensic mental health, deinstitutionalization, reintegration, mental health service users

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Authors: Reetinder Kaur, R. K. Pathak

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Mental health is recognised as an important global health concern. World Health Organisation in 2004 estimated that neuropsychiatric illnesses in India account for 10.8 percent of the global burden. The prevalence of serious mental illnesses is estimated as 6.5 percent by National Commission of Macroeconomics and Health in 2005. India spends only 0.06 percent of its health budget on mental health. One of the major problems that exist in Indian mental health care is the treatment gap due to scarcity of manpower, inadequate infrastructure and deficiencies in policy initiatives. As a result, traditional healing is a popular resource for mentally ill individuals and their families. The various traditional healing resources include faith healers, healers at temples and Dargahs. Chandigarh is a Union Territory located in North India. It has surplus manpower and infrastructure available for mental health care. Inspite of availability of mental health care services, mentally ill individuals and their families seek help from traditional healers at various Dargahs within or outside Chandigarh. For the present study, the data was collected from four dargahs. A total of thirty patients medically diagnosed with various mental illnesses, their family members who accompanied them and healers were part of this study. The aim of the study was to: Understand the interactions between healer, patient and family members during the course of treatment, understand explanations of mental illnesses and analyse the healing practices in context of culture. The interviews were conducted using an interview guide for the three sets of informants: Healers, patients and family members. The interview guide for healer focussed on the healing process, healer’s understanding of patient’s explanatory models, healer’s knowledge about mental illnesses and types of these illnesses cured by the healer. The interview guide for patients and family members focussed on their understanding of the symptoms, explanations for illness and help-seeking behaviour. The patients were observed over the weeks (every Thursday, the day of pir and healing) during their visits to the healer. Detailed discussions were made with the healer regarding the healing process and benefits of healing. The data was analysed thematically and the themes: The role of sacred, holistic healing, healer’s understanding of patient’s explanatory models of mental illness, the patient’s, and family’s understanding of mental illnesses, healer’s knowledge about mental illnesses, types of mental illnesses cured by the healer, bad dreams and their interpretation emerged. From the analysis of data, it was found that the healers concentrate their interventions in the social arena, ‘curing’ distressed patients by bringing significant changes in their social environment. It is suggested that in order to make the mental health care services effective in India, the collaboration between healers and psychiatrist is essential. However, certain specifications need to be made to make this kind of collaboration successful and beneficial for the stakeholders.

Keywords: Dargah, mental illness, traditional healing, policy

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

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Authors: Tara Hunter, Kristine Concepcion, Wendy Cheng, Brianna Pike, Jane Estoesta, Anne Stuart

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In 2015, Family Planning NSW was contracted by the NSW Ministry of Health to design and deliver Sexual Safety Policy training (SSPT) to mental health professionals across NSW. The training was based on their current guidelines and developed in consultation with an expert reference group. From October 2015 to April 2017 it was delivered to over 2,400 mental health professionals with a view to supporting implementation of consistent prevention and intervention related to sexual safety in the mental health setting. An evaluation was undertaken to determine the knowledge and confidence of participants related to sexual safety before and after the training, and whether any improvements were translated into changes in practice. Participants were invited to complete a survey prior to the training, upon completion and three to six months thereafter. Telephone interviews were conducted among service managers and mental health champions six months post-training. Prior to training, the majority of mental health professionals reported being slightly to moderately confident in identifying a sexual safety incident. When asked on their understanding of sexual safety, gender sensitive practice and trauma informed care, they reported no confidence, slight confidence and moderate confidence. Immediately after the training, 54.5% reported being very confident and 10.9% extremely confident in identifying a sexual safety incident. More than half felt very confident or extremely confident in their understanding of sexual safety principles. The impact survey (six months later) found that the majority of participants (91%) were highly confident in identifying a sexual safety incident. Telephone interviewees reported a change in workplace culture and increased awareness after the training. Mental health professionals experienced increased knowledge and confidence about sexual safety principles following the training and were able to implement positive changes and concrete actions to better address sexual safety issues in their workplace.

Keywords: sexual safety, mental health professionals, trauma informed care, policy training

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Authors: Bency Jacob, S.B. Waykar

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Degradations in historical document images appear due to aging of the documents. It is very difficult to understand and retrieve text from badly degraded documents as there is variation between the document foreground and background. Thresholding of such document images either result in broken characters or detection of false texts. Numerous algorithms exist that can separate text and background efficiently in the textual regions of the document; but portions of background are mistaken as text in areas that hardly contain any text. This paper presents a way to overcome these problems by a robust binarization technique that recovers the text from a severely degraded document images and thereby increases the accuracy of optical character recognition systems. The proposed document recovery algorithm efficiently removes degradations from document images. Here we are using the ostus method ,local thresholding and global thresholding and after the binarization training and recognizing the characters in the degraded documents.

Keywords: binarization, denoising, global thresholding, local thresholding, thresholding

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Authors: Seyed Reza Mirmahdi, Seyedeh Maryam Hashemi Jabali

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This research was conducted to evaluate the effects of group spiritual therapy on increasing the life expectancy and mental health among the elderlies. This was a quasi-experimental research using a pretest-posttest design with a control group conducted over a population including all the elderly people of Tehran in 2012-13. A randomized sampling method was used to select 30 elderly people living in Parham nursing home that were then randomly assigned into two control and experimental groups of 15 people each. The instruments used were Miller’s life expectancy and mental health test (SCL.90.R) standard questionnaires. Individuals in experimental group received 12 sessions of group spiritual therapy while those in control group did not receive any kind of therapy. The tests were performed again for all the subjects (30 individuals) at the end of the experiment. To test the hypotheses, the data collected by questionnaires were analyzed using descriptive methods through relevant tables and charts and also inferential methods through the analysis of covariance using the SPSS software. Results showed that group spiritual therapy leads to a significant increase in both mental health and life expectancy in the experimental group of elderlies living in Parham nursing home compared to those in the control group.

Keywords: spiritual therapy, life expectancy, mental health, elderlies

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Authors: Reji Thankachan, Varsha PS

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Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

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Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

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Authors: Saman Ghaffarian, Ilgin Gökaşar

Abstract:

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: 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: Zihan Yu, Kohei Inoue, Kiichi Urahama

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We present a method for de-hazing images. A dark envelope image is derived with the bilateral minimum filter and a bright envelope is derived with the bilateral maximum filter. The ambient light and transmission of the scene are estimated from these two envelope images. An image without haze is reconstructed from the estimated ambient light and transmission.

Keywords: image dehazing, bilateral minimum filter, bilateral maximum filter, local contrast

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Onyebueke Godwin, Okwarafor Friday

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Introduction: Persons with HIV/AIDS disease are predisposed to mental health disorders such as depression and suicide. HIV/AIDS, being a chronic medical illness with antecedent stigmatization ostracization, leads to low mood, low self-esteem, and a tendency to kill oneself due to the burden of the disease in terms of cost and disability. The aim of one study was to examine the prevalence of depression and risk of suicide among HIV/AIDS patients compared to negative persons. Instruments: The Major Depressive Episode and Suicidality modules of the MINI-Neuropsychiatric inventory were used to screen the attendees. Report: The prevalence of depression and risk of suicide were 27.8% and 7.8%, respectively, for the HIV positive subjects, but 1208% and 2.2%, respectively, for negative subjects. Conclusion and Significance: Persons with HIV/AIDS usually present with mental health symptoms, but the attending physicians usually pay attention to physical symptoms. The symptoms of the disease or the side effects of the medication may mask the mental health disease. Recommendation: There is need to screen HIV/AIDS patents for mental health disorders during clinic visits.

Keywords: depression, HIV/AIDS, suicidality

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Authors: Singara Singh Kasana, Pankaj Garg

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In this paper, a blind data hiding technique based on interpolation of sub sampled versions of a cover image is proposed. Sub sampled image is taken as a reference image and an interpolated image is generated from this reference image. Then difference between original cover image and interpolated image is used to embed secret data. Comparisons with the existing interpolation based techniques show that proposed technique provides higher embedding capacity and better visual quality marked images. Moreover, the performance of the proposed technique is more stable for different images.

Keywords: interpolation, image subsampling, PSNR, SIM

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Soowon Park, Min-Ji Kim, Jun-Young Lee

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Motivation: The stigma of mental illness has been studied in many disciplines, including social psychology, counseling psychology, sociology, psychiatry, public health care, and related areas, because individuals labeled as ‘mentally ill’ are often deprived of their rights and their life opportunities. To understand the factors that deepen the stigma of mental illness, it is important to understand the influencing factors of the stigma. Problem statement: Depression is a common disorder in adults, but the incidence of help-seeking is low. Researchers have believed that this poor help-seeking behavior is related to the stigma of mental illness, which results from low mental health literacy. However, it is uncertain that increasing mental health literacy decreases mental health stigmatization. Furthermore, even though decreasing stigmatization is important, the stigma of mental illness is still a stable and long-lasting phenomenon. Thus, factors other than knowledge about mental disorders have the power to maintain the stigma. Investigating the influencing factors that facilitate the stigma of psychiatric disease could help lower the social stigmatization. Approach: Face-to-face interviews were conducted with a multi-clustering sample. A total of 700 Korean participants (38% male), ranging in age from 18 to 78 (M(SD)age= 48.5(15.7)) answered demographical questions, Korean version of Link’s Perceived Devaluation and Discrimination (PDD) scale for the assessment of social stigmatization against depression, and the Korean version of the WHO-Composite International Diagnostic Interview for the assessment of mental disorders. Multiple-regression was conducted to find the predicting factors of social stigmatization against depression. Ages, sex, years of education, income, living location, and experience of mental illness were used as the predictors. Results: Predictors accounted for 14% of the variance in the stigma of depressive disorders (F(6, 693) = 20.27, p < .001). Among those, only age, years of education, and experience of mental illness significantly predicted social stigmatization against depression. The standardized regression coefficient of age had a negative association with stigmatization (β = -.20, p < .001), but years of education (β = .20, p < .001) and experience of mental illness (β = .08, p < .05) positively predicted depression stigmatization. Conclusions: The present study clearly demonstrates the association between personal factors and depressive disorder stigmatization. Younger age, more education, and self-stigma appeared to increase the stigmatization. Young, highly educated, and mentally ill people tend to reject patients with depressive disorder as friends, teachers, or babysitters; they also tend to think that those patients have lower intelligence and abilities. These results suggest the possibility that people from a high social class, or highly educated people, who have the power to make decisions, help maintain the social stigma against mental illness patients. To increase the awareness that people from high social classes have more stigmatization against depressive disorders will help decrease the biased attitudes against mentally ill patients.

Keywords: depressive disorder stigmatization, age, education, self-stigma

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Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

Abstract:

Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

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Authors: Denise Ben-Porath, Tracy Masterson

Abstract:

In the past, individuals who struggled with and sought treatment for mental health difficulties were stigmatized. However, the current generation holds more open attitudes around mental health issues. Indeed, public figures such as Demi Lovato, Naomi Osaka, and Simone Biles have taken to social media to break the silence around mental health, discussing their own struggles and the benefits of treatment. Thus, there is considerable reason to believe that this generation would hold fewer stigmatizing attitudes toward mental health difficulties and treatment compared to previous ones. In this study, we explored possible changes in stigma on mental health diagnosis and treatment seeking behavior between two generations: Gen Z, the current generation, and Gen X, those born between 1965-1980. It was hypothesized that Gen Z would hold less stigmatizing views on mental illness than Gen X. To examine possible changes in stigma attitudes between these two generations, we conducted a cross-generational cohort design by using the same methodology employed 20 years ago from the Ben-Porath (2002) study. Thus, participants were randomly assigned to read one of the following four case vignettes employed in the Ben-Porath (2002) study: (a) “Tom” who has received psychotherapy due to depression (b) “Tom” who has been depressed but received no psychological help, (c) “Tom” who has received medical treatment due to a back pain, or (d) “Tom” who had a back pain but did not receive medical attention. After reading the vignette, participants rated “Tom” on various personality dimensions using the IFQ Questionnaire and answered questions about their frequency of social media use and willingness to seek mental health treatment on a scale from 1-10. Identical to the results 20 years prior, a significant main effect was found for diagnosis with “Tom” being viewed in more negative terms when he was described as having depression vs. a medical condition (back pain) [F (1, 376) = 126.53, p < .001]. However, in the study conducted 20 years earlier, a significant interaction was found between diagnosis and help-seeking behavior [F (1, 376) = 8.28, p < .005]. Specifically, “Tom” was viewed in the most negative terms when described as depressed and seeking treatment. Alternatively, the current study failed to find a significant interaction between depression and help seeking behavior. These findings suggest that while individuals who hold a mental health diagnosis may still be stigmatized as they were 20 years prior, seeking treatment for mental health issues may be less so. Findings are discussed in the context of social media use and its impact on destigmatization.

Keywords: stigma, mental illness, help-seeking, social media

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Authors: Shatha Ahmad Alharthi

Abstract:

Prior research suggests that reduced social interaction can negatively affect well-being and impair mental health (e.g., depression and anxiety), resulting in lower academic performance. The COVID-19 pandemic has significantly limited social interaction among Saudi Arabian school children since the government closed schools and implemented lockdown restrictions to reduce the spread of the disease. These restrictions have resulted in prolonged remote learning for middle school students with unknown consequences for perceived academic performance, mental health, and well-being. This research project explores how middle school Saudi students’ current remote learning practices affect their mental health (e.g., depression and anxiety) and well-being during the lockdown. Furthermore, the study will examine the association between social interaction, mental health, and well-being pertaining to students’ perceptions of their academic achievement. Research findings could lead to a better understanding of the role of lockdown on depression, anxiety, well-being and perceived academic performance. Research findings may also inform policy-makers or practitioners (e.g., teachers and school leaders) about the importance of facilitating increased social interactions in remote learning situations and help to identify important factors to consider when seeking to re-integrate students into a face-to-face classroom setting. Potential implications for future educational research include exploring remote learning interventions targeted at bolstering students’ mental health and academic achievement during periods of remote learning.

Keywords: depression, anxiety, academic performance, social interaction

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Authors: Szu-Yi Chang, Jiin-Ru Rong

Abstract:

This paper discussed a case involving a young female patient with schizophrenia. The patient's condition was deteriorating, and she was becoming increasingly reliant on her family to take care of her, and as her father did not understand the illness well and was afraid that others will learn about the presence of a mentally ill individual in their family, he and the patient's mother were thus unable to cope with the patient's deteriorating condition, which in turn caused her to suffer from a lack of self-confidence and low self-esteem. The patient received nursing care from July 26th to October 25th, 2017, during which counseling, family visits, and phone interviews were carried out, and her condition was monitored. By referring to the practical ability indicators for community psychiatric mental health nursing that were developed by the psychiatric mental health nurses' association of the Republic of China, defining categories such as 'self-construction,' 'self-management,' 'disease management,' and 'family nursing,' and incorporating indicators for empowerment and various skills into the steps and strategies used for nursing care, we will able to help the patient to construct her own identity, raise her self-esteem, improve her ability to independently perform activities of daily living, strengthen her disease management ability, and gradually build up her life management skills. The patient's family was also encouraged to communicate more among themselves, so as to align them with the nursing care objectives of improving the patient's ability to adapt to community life and her disease. The results indicated that the patient was able to maintain her mental stability within her community. By implementing effective self-management and maintaining a routine life, the patient was able to continue her active participation in community work and rehabilitation activities. Improvements were also achieved with respect to family role issues by establishing mutual understanding among the patient's family members and gaining their support. It is recommended that mental health nurses can leverage their community mental health nursing skills and the related strategies to promote adaptation to community life among mental life patients.

Keywords: community psychiatric mental health nursing, family nursing, schizophrenia, self-management

Procedia PDF Downloads 278