Search results for: medical image analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31911

Search results for: medical image analysis

30981 Field Emission Scanning Microscope Image Analysis for Porosity Characterization of Autoclaved Aerated Concrete

Authors: Venuka Kuruwita Arachchige Don, Mohamed Shaheen, Chris Goodier

Abstract:

Aerated autoclaved concrete (AAC) is known for its lightweight, easy handling, high thermal insulation, and extremely porous structure. Investigation of pore behavior in AAC is crucial for characterizing the material, standardizing design and production techniques, enhancing the mechanical, durability, and thermal performance, studying the effectiveness of protective measures, and analyzing the effects of weather conditions. The significant details of pores are complicated to observe with acknowledged accuracy. The High-resolution Field Emission Scanning Electron Microscope (FESEM) image analysis is a promising technique for investigating the pore behavior and density of AAC, which is adopted in this study. Mercury intrusion porosimeter and gas pycnometer were employed to characterize porosity distribution and density parameters. The analysis considered three different densities of AAC blocks and three layers in the altitude direction within each block. A set of understandings was presented to extract and analyze the details of pore shape, pore size, pore connectivity, and pore percentages from FESEM images of AAC. Average pore behavior outcomes per unit area were presented. Comparison of porosity distribution and density parameters revealed significant variations. FESEM imaging offered unparalleled insights into porosity behavior, surpassing the capabilities of other techniques. The analysis conducted from a multi-staged approach provides porosity percentage occupied by various pore categories, total porosity, variation of pore distribution compared to AAC densities and layers, number of two-dimensional and three-dimensional pores, variation of apparent and matrix densities concerning pore behaviors, variation of pore behavior with respect to aluminum content, and relationship among shape, diameter, connectivity, and percentage in each pore classification.

Keywords: autoclaved aerated concrete, density, imaging technique, microstructure, porosity behavior

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30980 Derivation of Bathymetry Data Using Worldview-2 Multispectral Images in Shallow, Turbid and Saline Lake Acıgöl

Authors: Muhittin Karaman, Murat Budakoglu

Abstract:

In this study, derivation of lake bathymetry was evaluated using the high resolution Worldview-2 multispectral images in the very shallow hypersaline Lake Acıgöl which does not have a stable water table due to the wet-dry season changes and industrial usage. Every year, a great part of the lake water budget has been consumed for the industrial salt production in the evaporation ponds, which are generally located on the south and north shores of Lake Acıgöl. Therefore, determination of the water level changes from a perspective of remote sensing-based lake water by bathymetry studies has a great importance in the sustainability-control of the lake. While the water table interval is around 1 meter between dry and wet season, dissolved ion concentration, salinity and turbidity also show clear differences during these two distinct seasonal periods. At the same time, with the satellite data acquisition (June 9, 2013), a field study was conducted to collect the salinity values, Secchi disk depths and turbidity levels. Max depth, Secchi disk depth and salinity were determined as 1,7 m, 0,9 m and 43,11 ppt, respectively. Eight-band Worldview-2 image was corrected for atmospheric effects by ATCOR technique. For each sampling point in the image, mean reflectance values in 1*1, 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15, 17*17, 19*19, 21*21, 51*51 pixel reflectance neighborhoods were calculated separately. A unique image has been derivated for each matrix resolution. Spectral values and depth relation were evaluated for these distinct resolution images. Correlation coefficients were determined for the 1x1 matrix: 0,98, 0,96, 0,95 and 0,90 for the 724 nm, 831 nm, 908 nm and 659 nm, respectively. While 15x5 matrix characteristics with 0,98, 0,97 and 0,97 correlation values for the 724 nm, 908 nm and 831 nm, respectively; 51x51 matrix shows 0,98, 0,97 and 0,96 correlation values for the 724 nm, 831 nm and 659 nm, respectively. Comparison of all matrix resolutions indicates that RedEdge band (724 nm) of the Worldview-2 satellite image has the best correlation with the saline shallow lake of Acıgöl in-situ depth.

Keywords: bathymetry, Worldview-2 satellite image, ATCOR technique, Lake Acıgöl, Denizli, Turkey

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30979 Infertility Awareness: Knowledge and Attitude of Medical & Non-Medical Moroccan Young People

Authors: Sana El Adlani, Yassir Ait Ben Kaddour, Abdelhafid Benksim, Abderraouf Soummani, Mohamed Cherkaoui

Abstract:

Background: Infertility in all countries of the word is on an increase, it’s why the World Health Organization included an investigation into young people's fertility. In this sense, it’s important to increase efforts to improve the knowledge about fertility for the young population. The aim of this study is to describe the difference between knowledge and attitude of medical and non-medical Moroccan young people. Materials and Methods: 100 medical Moroccan students (group 1) participated in the study, between 18 and 30 years, by a simple random sampling method, during 2020 and using a previously validated questionnaire. The answers were confronted to the result of our same study among 355 non-medical Moroccan young people (group 2) in 2019. Statistical analyses were performed using Statistical Package for the Social Sciences (version 10). Result: Medical students had a significantly higher level of knowledge about infertility than non-medical young people. However, both groups were aware of the impact of lifestyle on infertility. The knowledge state of the first group about infertility management was higher than the second group. Moreover, all non-medical Moroccan young people believed that it is easier to conceive if the couples had already their first baby, whereas, among medical students, only 53% had confirmed this belief. The results showed that 65% of medical students had proposed to try fertility treatments more than one time if treatment fails. Besides, the first advice of the second group was polygamy and adoption. Conclusion: Following the result of our study, the investigation of young people is the measure to optimize reproductive health. So, it’s crucial that the government increase efforts to improve the knowledge about infertility not only for medical universities but for all scholar programs.

Keywords: attitude, infertility, knowledge, medical, non-medical, young people

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30978 Effect of Mindfulness-Based Self-Care Training on Self-Esteem and Body Image Concern on Candidate Patients of Orthognathic Surgery

Authors: Hamide Azimi Lolaty, Fateme Alsadat Ghanipoor, Azar Ramzani, Reza Ali Mohammadpoor, Alireza Babaei

Abstract:

Background and Objective: Despite the merits behind orthognathic surgery, self-care training in such patients seems logical. The current research was performed pursuing the goal of outlining the effect of training mindfulness-based self-care on Self-Esteem (SE) and Body Image Concern (BIC) of orthognathic surgery candidate patients. Material and Methods: The present study was performed using a semi-experimental method with pre-and post-design in the control and intervention groups. The eligible patients to enter the Babol-based Shahid Beheshti Orthognathic Surgery Clinic were conveniently divided into two 25-person groups. The variables of Self-Esteem and Body Image Concern were measured before and after executing the eight 90-minute training sessions and in the follow-up period done three months after executing the intervention using Cooper Smith’s Self-Esteem Inventory (CSEI) and Body Image Concern Inventory (BICI). The data were analyzed using ANOVA and the independent t-test and using SPSS-26, the data were analyzed at a 0.05 level. Results: As a result of the intervention, the intervention group’s SE score critically changed on average from 25.4±7.31 in the pre-intervention to 31.16±7.05 in the post-intervention and to 40.45±3.51 in the follow-up period (P=0.01), the intervention group’s BIC score changed on average from 60.28±16.47 in the pre-intervention to 47.15±80.47 in the post-intervention and to 32.20 ± 10.73 in the follow-up period. This difference was meaningful (P=0.001). But due to time and the intervention interaction, the control group underwent this significant reduction with a delay. The study revealed the scores of the SE as 32± 6.84 and that of the BIC as 43.32±10.64 in the control group didn’t result in any meaningful statistical difference (P<0.05). Conclusion: Training mindfulness-based self-care exerts an effect on the SE and BIC of the patients undergoing orthognathic surgery. Therefore, it’s recommended to train mindfulness-based self-care for orthognathic surgery candidate patients.

Keywords: self-care, mindfulness, self-esteem, body image concern, orthognathic surgery

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30977 Image Segmentation with Deep Learning of Prostate Cancer Bone Metastases on Computed Tomography

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

Abstract:

Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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30976 Local Spectrum Feature Extraction for Face Recognition

Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

Abstract:

This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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30975 Adaptation of Hough Transform Algorithm for Text Document Skew Angle Detection

Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

Abstract:

The skew detection and correction form an important part of digital document analysis. This is because uncompensated skew can deteriorate document features and can complicate further document image processing steps. Efficient text document analysis and digitization can rarely be achieved when a document is skewed even at a small angle. Once the documents have been digitized through the scanning system and binarization also achieved, document skew correction is required before further image analysis. Research efforts have been put in this area with algorithms developed to eliminate document skew. Skew angle correction algorithms can be compared based on performance criteria. Most important performance criteria are accuracy of skew angle detection, range of skew angle for detection, speed of processing the image, computational complexity and consequently memory space used. The standard Hough Transform has successfully been implemented for text documentation skew angle estimation application. However, the standard Hough Transform algorithm level of accuracy depends largely on how much fine the step size for the angle used. This consequently consumes more time and memory space for increase accuracy and, especially where number of pixels is considerable large. Whenever the Hough transform is used, there is always a tradeoff between accuracy and speed. So a more efficient solution is needed that optimizes space as well as time. In this paper, an improved Hough transform (HT) technique that optimizes space as well as time to robustly detect document skew is presented. The modified algorithm of Hough Transform presents solution to the contradiction between the memory space, running time and accuracy. Our algorithm starts with the first step of angle estimation accurate up to zero decimal place using the standard Hough Transform algorithm achieving minimal running time and space but lacks relative accuracy. Then to increase accuracy, suppose estimated angle found using the basic Hough algorithm is x degree, we then run again basic algorithm from range between ±x degrees with accuracy of one decimal place. Same process is iterated till level of desired accuracy is achieved. The procedure of our skew estimation and correction algorithm of text images is implemented using MATLAB. The memory space estimation and process time are also tabulated with skew angle assumption of within 00 and 450. The simulation results which is demonstrated in Matlab show the high performance of our algorithms with less computational time and memory space used in detecting document skew for a variety of documents with different levels of complexity.

Keywords: hough-transform, skew-detection, skew-angle, skew-correction, text-document

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30974 Website Appeal’s Impact on Brand Outcomes: The Mediated Effect of Emotional Attractiveness in the Relationship between Consistent Image and Brand Value

Authors: Salvador Treviño-Martinez, Christian Reich-Lopez

Abstract:

This paper investigates the relationship between website appeal and brand value outcomes (brand attraction, brand loyalty, brand relationship, and brand experience), considering the mediating effect of emotional attractiveness. Data were collected from 221 customers of a quick-service restaurant in Culiacan, Mexico, using an online survey distributed via WhatsApp, following the clients' navigation of the restaurant's website. The study employed PLS-SEM to test the proposed hypotheses and performed 5,000 bootstrapping subsamples to obtain results. The findings indicate that consistent image, a key component of website appeal, has a statistically significant direct and mediated effect (through emotional attractiveness) on the aforementioned brand outcomes. The study's limitations include the convenience sampling method and the single company client database used for the sample composition. This research contributes to the branding and website quality literature by testing nine hypotheses using the Stimuli-Organism-Response theoretical approach in an underexplored context: quick-service restaurants in Latin America.

Keywords: website appeal, branding, emotional attractiveness, consistent image, website quality

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30973 Image Based Landing Solutions for Large Passenger Aircraft

Authors: Thierry Sammour Sawaya, Heikki Deschacht

Abstract:

In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

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30972 Reasons for Choosing Medicine and the Personality Traits of Pre-Clinical Medical Students

Authors: Zarini Ismail, Nurul Azmawati Mohamed, Shalinawati Ramli, Nurul Hayati Chamhuri, Nur Syahrina Rahim, Khairani Omar

Abstract:

Choosing a career is one of the most important decisions that people have to make in life. While choosing a suitable career, a person cannot ignore their intrinsic traits such as the type of personality, interests, values, and aptitude. The objective of this study is to ascertain the personality of the pre-clinical medical students and their reasons or intentions for choosing medicine as a career. This study is a cross-sectional study involving Year 3 pre-clinical medical students at Universiti Sains Islam Malaysia. Participants were given a set of validated questionnaires on demographic data and open-ended questions for reasons of choosing medicine. Thematic analysis were used to analyse the open-ended question. The Participants were also required to answer a Career Interest Questionnaire (based on Holland’s Theory). A total of 81 Year 3 medical students were involved in this study. About two third (69%) of them were female and their age ranged from 20 to 21 years old. The majority of them were from middle-income families. From the thematic analysis, there were several reasons given for choosing medicine by the students. The majority of the students stated that it was their passion and interest in the medical field (45.7%). Approximately 24.7% decided to take the medical course because of parents/family influenced and 19.8% mentioned that they wanted to help the society. Other themes emerged were jobs opportunity in future (1.2%) and influenced by friends (3.7%). Based on Holland’s theory, ideally to become a good medical doctor one should score high in investigative and social personality trait. However, 26.3% of the students had low scores in these personality traits. We then looked into the reasons given by these students for choosing medicine. Approximately 28% were due to parents/family decision while 52% admitted that it was due to their interest. When compared with the group of students with high personality scores (investigative and social), there was not much difference in the reasons given for choosing medicine. The main reasons given by the students for choosing medicine were own interest, family’s influence and to help others. However, a proportion of them had low scores in the personality traits which are relevant for medicine. Although some of these students admitted that they choose medicine based on their interest, their strength might not be suitable for their chosen carrier.

Keywords: career, medical students, medicine, personality

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30971 The Implication of Small Group Therapy on Sexuality in Breast Cancer Survivors

Authors: Cherng-Jye Jeng, Ming-Feng Hou, Hsing-Yuan Liu, Chuan-Feng Chang, Lih-Rong Wang, Yen-Chin Lin

Abstract:

Introduction: The incidence of breast cancer has gradually increased in Taiwan, and the characteristic of younger ages impact these women in their middle age, and may also cause challenges in terms of family, work, and illness. Breasts are symbols of femininity, as well as of sex. For women, breasts are important organs for the female identity and sexual expression. Losing breasts not only affects the female role, but would also affect sexual attraction and sexual desire. Thus, women with breast cancer who have need for mastectomies experience physical incompletion, which affects women’s self-confidence, physical image, and self-orientation. Purposes: 1. To understand the physical experience of women with breast cancer. 2. To explore the issue of sexual issues on the health effects of women with breast cancer. 3. To construct a domestic sex life issue group model for domestic women with breast cancer. 4. To explore the accompaniment experiences and sexual relationship adjustments of spouses when women have breast cancer. Method: After the research plan passes IRB review, participants will be recruited at breast surgery clinic in the affiliated hospital, to screen suitable subjects for entry into the group. Between March and May 2015, two sexual health and sex life consultation groups were conducted, which were (1) 10 in postoperative groups for women with cancer; (2) 4 married couples group for postoperative women with cancer. After sharing experiences and dialogue, women can achieve mutual support and growth. Data organization and analysis underwent descriptive analysis in qualitative research, and the group process was transcribed into transcripts for overall-content and category-content analysis. Results: Ten women with breast cancer believed that participating in group can help them exchange experiences, and elevate sexual health. The main issues include: (1) after breast cancer surgery, patients generally received chemotherapy or estrogen suppressants, causing early menopause; in particular, vaginal dryness can cause pain or bleeding in intercourse, reducing their desire for sexual activity; (2) breast cancer accentuates original spousal or family and friend relationships; some people have support and care from their family, and spouses emphasize health over the appearance of breasts; however, some people do not have acceptance and support from their family, and some even hear spousal sarcasm about loss of breasts; (3) women with breast cancer have polarized expressions of optimism and pessimism in regards to their emotions, beliefs, and body image regarding cancer; this is related to the women’s original personalities, attribution of causes of cancer, and extent of worry about relapse. Conclusion: The research results can be provided as a reference to medical institutions or breast cancer volunteer teams, to pay attention to maintaining the health of women with breast cancer.

Keywords: women with breast cancer, experiences of objectifying the body, quality of sex life, sexual health

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30970 Rigorous Photogrammetric Push-Broom Sensor Modeling for Lunar and Planetary Image Processing

Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

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30969 Grid Pattern Recognition and Suppression in Computed Radiographic Images

Authors: Igor Belykh

Abstract:

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

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30968 Application of Electrical Resistivity Tomography to Image the Subsurface Structure of a Sinkhole, a Case Study in Southwestern Missouri

Authors: Shishay T. Kidanu

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The study area is located in Southwestern Missouri and is mainly underlain by Mississippian Age limestone which is highly susceptible to karst processes. The area is known for the presence of various karst features like caves, springs and more importantly Sinkholes. Sinkholes are one of the most common karst features and the primary hazard in karst areas. Investigating the subsurface structure and development mechanism of existing sinkholes enables to understand their long-term impact and chance of reactivation and also helps to provide effective mitigation measures. In this study ERT (Electrical Resistivity Tomography), MASW (Multichannel Analysis of Surface Waves) and borehole control data have been used to image the subsurface structure and investigate the development mechanism of a sinkhole in Southwestern Missouri. The study shows that the main process responsible for the development of the sinkhole is the downward piping of fine grained soils. Furthermore, the study reveals that the sinkhole developed along a north-south oriented vertical joint set characterized by a vertical zone of water seepage and associated fine grained soil piping into preexisting fractures.

Keywords: ERT, Karst, MASW, sinkhole

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30967 Developing Rice Disease Analysis System on Mobile via iOS Operating System

Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

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This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: rice disease, data analysis system, mobile application, iOS operating system

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30966 Life Expansion: Autobiography, Ficctionalized Digital Diaries and Forged Narratives of Everyday Life on Instagram

Authors: Pablo M. S. Vallejos

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The article aims to analyze the autobiographical practices of users on Instagram, observing the instrumentalization of image resources in the construction of visual narratives that make up that archive and digital diary. Through bibliographical review, discourse exploration and case studies, the research also aims to present a new theoretical perception about everyday records - edited with a collage of filters and aesthetic tools - that permeate that social network, understanding it as a platform fictionalizing and an expansion of life. In this way, therefore, the work reflects on possible futures in the elaboration of representations and identities in the context of digital spaces in the 21st century.

Keywords: visual culture, social media, autobiography, image

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30965 Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier

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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30964 Experimental Investigation of the Aeroacoustics Field for a Rectangular Jet Impinging on a Slotted Plate: Stereoscopic Particle Image Velocimetry Measurement before and after the Plate

Authors: Nour Eldin Afyouni, Hassan Assoum, Kamel Abed-Meraim, Anas Sakout

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The acoustic of an impinging jet holds significant importance in the engineering field. In HVAC systems, the jet impingement, in some cases, generates noise that destroys acoustic comfort. This paper presents an experimental study of a rectangular air jet impinging on a slotted plate to investigate the correlation between sound emission and turbulence dynamics. The experiment was conducted with an impact ratio L/H = 4 and a Reynolds number Re = 4700. The survey shows that coherent structures within the impinging jet are responsible for self-sustaining tone production. To achieve this, a specific experimental setup consisting of two simultaneous Stereoscopic Particle Image Velocimetry (S-PIV) measurements was developed to track vortical structures both before and after the plate, in addition to acoustic measurements. The results reveal a significant correlation between acoustic waves and the passage of coherent structures. Variations in the arrangement of vortical structures between the upstream and downstream sides of the plate were observed. This analysis of flow dynamics can enhance our understanding of slot noise.

Keywords: impinging jet, coherent structures, SPIV, aeroacoustics

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30963 Decision Tree Analysis of Risk Factors for Intravenous Infiltration among Hospitalized Children: A Retrospective Study

Authors: Soon-Mi Park, Ihn Sook Jeong

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This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

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30962 A Nonlinear Parabolic Partial Differential Equation Model for Image Enhancement

Authors: Tudor Barbu

Abstract:

We present a robust nonlinear parabolic partial differential equation (PDE)-based denoising scheme in this article. Our approach is based on a second-order anisotropic diffusion model that is described first. Then, a consistent and explicit numerical approximation algorithm is constructed for this continuous model by using the finite-difference method. Finally, our restoration experiments and method comparison, which prove the effectiveness of this proposed technique, are discussed in this paper.

Keywords: anisotropic diffusion, finite differences, image denoising and restoration, nonlinear PDE model, anisotropic diffusion, numerical approximation schemes

Procedia PDF Downloads 314
30961 An 8-Bit, 100-MSPS Fully Dynamic SAR ADC for Ultra-High Speed Image Sensor

Authors: F. Rarbi, D. Dzahini, W. Uhring

Abstract:

In this paper, a dynamic and power efficient 8-bit and 100-MSPS Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) is presented. The circuit uses a non-differential capacitive Digital-to-Analog (DAC) architecture segmented by 2. The prototype is produced in a commercial 65-nm 1P7M CMOS technology with 1.2-V supply voltage. The size of the core ADC is 208.6 x 103.6 µm2. The post-layout noise simulation results feature a SNR of 46.9 dB at Nyquist frequency, which means an effective number of bit (ENOB) of 7.5-b. The total power consumption of this SAR ADC is only 1.55 mW at 100-MSPS. It achieves then a figure of merit of 85.6 fJ/step.

Keywords: CMOS analog to digital converter, dynamic comparator, image sensor application, successive approximation register

Procedia PDF Downloads 418
30960 A Cognitive Semantic Analysis of the Metaphorical Extensions of Come out and Take Over

Authors: Raquel Rossini, Edelvais Caldeira

Abstract:

The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

Procedia PDF Downloads 155
30959 A Four-Step Ortho-Rectification Procedure for Geo-Referencing Video Streams from a Low-Cost UAV

Authors: B. O. Olawale, C. R. Chatwin, R. C. D. Young, P. M. Birch, F. O. Faithpraise, A. O. Olukiran

Abstract:

Ortho-rectification is the process of geometrically correcting an aerial image such that the scale is uniform. The ortho-image formed from the process is corrected for lens distortion, topographic relief, and camera tilt. This can be used to measure true distances, because it is an accurate representation of the Earth’s surface. Ortho-rectification and geo-referencing are essential to pin point the exact location of targets in video imagery acquired at the UAV platform. This can only be achieved by comparing such video imagery with an existing digital map. However, it is only when the image is ortho-rectified with the same co-ordinate system as an existing map that such a comparison is possible. The video image sequences from the UAV platform must be geo-registered, that is, each video frame must carry the necessary camera information before performing the ortho-rectification process. Each rectified image frame can then be mosaicked together to form a seamless image map covering the selected area. This can then be used for comparison with an existing map for geo-referencing. In this paper, we present a four-step ortho-rectification procedure for real-time geo-referencing of video data from a low-cost UAV equipped with multi-sensor system. The basic procedures for the real-time ortho-rectification are: (1) Decompilation of video stream into individual frames; (2) Finding of interior camera orientation parameters; (3) Finding the relative exterior orientation parameters for each video frames with respect to each other; (4) Finding the absolute exterior orientation parameters, using self-calibration adjustment with the aid of a mathematical model. Each ortho-rectified video frame is then mosaicked together to produce a 2-D planimetric mapping, which can be compared with a well referenced existing digital map for the purpose of georeferencing and aerial surveillance. A test field located in Abuja, Nigeria was used for testing our method. Fifteen minutes video and telemetry data were collected using the UAV and the data collected were processed using the four-step ortho-rectification procedure. The results demonstrated that the geometric measurement of the control field from ortho-images are more reliable than those from original perspective photographs when used to pin point the exact location of targets on the video imagery acquired by the UAV. The 2-D planimetric accuracy when compared with the 6 control points measured by a GPS receiver is between 3 to 5 meters.

Keywords: geo-referencing, ortho-rectification, video frame, self-calibration

Procedia PDF Downloads 478
30958 Poor Medical Waste Management (MWM) Practices and Its Risks to Human Health and the Environment

Authors: Babanyara Y. Y., Ibrahim D. B., Garba T., Bogoro A. G., Abubakar, M. Y.

Abstract:

Medical care is vital for our life, health, and well-being. However, the waste generated from medical activities can be hazardous, toxic, and even lethal because of their high potential for diseases transmission. The hazardous and toxic parts of waste from healthcare establishments comprising infectious, medical, and radioactive material as well as sharps constitute a grave risks to mankind and the environment, if these are not properly treated/disposed or are allowed to be mixed with other municipal waste. In Nigeria, practical information on this aspect is inadequate and research on the public health implications of poor management of medical wastes is few and limited in scope. Findings drawn from Literature particularly in the third world countries highlights financial problems, lack of awareness of risks involved in MWM, lack of appropriate legislation and lack of specialized MWM staff. The paper recommends how MWM practices can be improved in medical facilities.

Keywords: environmental pollution, infectious, management, medical waste, public health

Procedia PDF Downloads 310
30957 Determination of Johnson-Cook Material and Failure Model Constants for High Tensile Strength Tendon Steel in Post-Tensioned Concrete Members

Authors: I. Gkolfinopoulos, N. Chijiwa

Abstract:

To evaluate the remaining capacity in concrete tensioned members, it is important to accurately estimate damage in precast concrete tendons. In this research Johnson-Cook model and damage parameters of high-strength steel material were calculated by static and dynamic uniaxial tensile tests. Replication of experimental results was achieved through finite element analysis for both single 8-noded three-dimensional element as well as the full-scale dob-bone shaped model and relevant model parameters are proposed. Finally, simulation results in terms of strain and deformation were verified using digital image correlation analysis.

Keywords: DIC analysis, Johnson-Cook, quasi-static, dynamic, rupture, tendon

Procedia PDF Downloads 147
30956 An Intelligent Nondestructive Testing System of Ultrasonic Infrared Thermal Imaging Based on Embedded Linux

Authors: Hao Mi, Ming Yang, Tian-yue Yang

Abstract:

Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

Procedia PDF Downloads 224
30955 Digital Material Characterization Using the Quantum Fourier Transform

Authors: Felix Givois, Nicolas R. Gauger, Matthias Kabel

Abstract:

The efficient digital material characterization is of great interest to many fields of application. It consists of the following three steps. First, a 3D reconstruction of 2D scans must be performed. Then, the resulting gray-value image of the material sample is enhanced by image processing methods. Finally, partial differential equations (PDE) are solved on the segmented image, and by averaging the resulting solutions fields, effective properties like stiffness or conductivity can be computed. Due to the high resolution of current CT images, the latter is typically performed with matrix-free solvers. Among them, a solver that uses the explicit formula of the Green-Eshelby operator in Fourier space has been proposed by Moulinec and Suquet. Its algorithmic, most complex part is the Fast Fourier Transformation (FFT). In our talk, we will discuss the potential quantum advantage that can be obtained by replacing the FFT with the Quantum Fourier Transformation (QFT). We will especially show that the data transfer for noisy intermediate-scale quantum (NISQ) devices can be improved by using appropriate boundary conditions for the PDE, which also allows using semi-classical versions of the QFT. In the end, we will compare the results of the QFT-based algorithm for simple geometries with the results of the FFT-based homogenization method.

Keywords: most likelihood amplitude estimation (MLQAE), numerical homogenization, quantum Fourier transformation (QFT), NISQ devises

Procedia PDF Downloads 78
30954 View Synthesis of Kinetic Depth Imagery for 3D Security X-Ray Imaging

Authors: O. Abusaeeda, J. P. O. Evans, D. Downes

Abstract:

We demonstrate the synthesis of intermediary views within a sequence of X-ray images that exhibit depth from motion or kinetic depth effect in a visual display. Each synthetic image replaces the requirement for a linear X-ray detector array during the image acquisition process. Scale invariant feature transform, SIFT, in combination with epipolar morphing is employed to produce synthetic imagery. Comparison between synthetic and ground truth images is reported to quantify the performance of the approach. Our work is a key aspect in the development of a 3D imaging modality for the screening of luggage at airport checkpoints. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, KDE, view synthesis

Procedia PDF Downloads 265
30953 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line

Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

Abstract:

Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

Procedia PDF Downloads 161
30952 A Framework of Product Information Service System Using Mobile Image Retrieval and Text Mining Techniques

Authors: Mei-Yi Wu, Shang-Ming Huang

Abstract:

The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

Procedia PDF Downloads 359