Search results for: ultrasound images.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2749

Search results for: ultrasound images.

1699 Study of Ultrasonic Waves in Unidirectional Fiber-Reinforced Composite Plates for the Aerospace Applications

Authors: DucTho Le, Duy Kien Dao, Quoc Tinh Bui, Haidang Phan

Abstract:

The article is concerned with the motion of ultrasonic guided waves in a unidirectional fiber-reinforced composite plate under acoustic sources. Such unidirectional composite material has orthotropic elastic properties as it is very stiff along the fibers and rather compliant across the fibers. The dispersion equations of free Lamb waves propagating in an orthotropic layer are derived that results in the dispersion curves. The connection of these equations to the Rayleigh-Lamb frequency relations of isotropic plates is discussed. By the use of reciprocity in elastodynamics, closed-form solutions of elastic wave motions subjected to time-harmonic loads in the layer are computed in a simple manner. We also consider the problem of Lamb waves generated by a set of time-harmonic sources. The obtained computations can be very useful for developing ultrasound-based methods for nondestructive evaluation of composite structures.

Keywords: lamb waves, fiber-reinforced composite plates, dispersion equations, nondestructive evaluation, reciprocity theorems

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1698 Application of Medical Information System for Image-Based Second Opinion Consultations–Georgian Experience

Authors: Kldiashvili Ekaterina, Burduli Archil, Ghortlishvili Gocha

Abstract:

Introduction – Medical information system (MIS) is at the heart of information technology (IT) implementation policies in healthcare systems around the world. Different architecture and application models of MIS are developed. Despite of obvious advantages and benefits, application of MIS in everyday practice is slow. Objective - On the background of analysis of the existing models of MIS in Georgia has been created a multi-user web-based approach. This presentation will present the architecture of the system and its application for image based second opinion consultations. Methods – The MIS has been created with .Net technology and SQL database architecture. It realizes local (intranet) and remote (internet) access to the system and management of databases. The MIS is fully operational approach, which is successfully used for medical data registration and management as well as for creation, editing and maintenance of the electronic medical records (EMR). Five hundred Georgian language electronic medical records from the cervical screening activity illustrated by images were selected for second opinion consultations. Results – The primary goal of the MIS is patient management. However, the system can be successfully applied for image based second opinion consultations. Discussion – The ideal of healthcare in the information age must be to create a situation where healthcare professionals spend more time creating knowledge from medical information and less time managing medical information. The application of easily available and adaptable technology and improvement of the infrastructure conditions is the basis for eHealth applications. Conclusion - The MIS is perspective and actual technology solution. It can be successfully and effectively used for image based second opinion consultations.

Keywords: digital images, medical information system, second opinion consultations, electronic medical record

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1697 Determination of the Local Elastic Moduli of Shungite by Laser Ultrasonic Spectroscopy

Authors: Elena B. Cherepetskaya, Alexander A.Karabutov, Vladimir A. Makarov, Elena A. Mironova, Ivan A. Shibaev

Abstract:

In our study, the object of laser ultrasonic testing was plane-parallel plate of shungit (length 41 mm, width 31 mm, height 15 mm, medium exchange density 2247 kg/m3). We used laser-ultrasonic defectoscope with wideband opto-acoustic transducer in our investigation of the velocities of longitudinal and shear elastic ultrasound waves. The duration of arising elastic pulses was less than 100 ns. Under known material thickness, the values of the velocities were determined by the time delay of the pulses reflected from the bottom surface of the sample with respect to reference pulses. The accuracy of measurement was 0.3% in the case of longitudinal wave velocity and 0.5% in the case of shear wave velocity (scanning pitch along the surface was 2 mm). On the base of found velocities of elastic waves, local elastic moduli of shungit (Young modulus, shear modulus and Poisson's ratio) were uniquely determined.

Keywords: laser ultrasonic testing , local elastic moduli, shear wave velocity, shungit

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1696 Subacute Thyroiditis Triggered by Sinovac and Oxford-AstraZeneca Vaccine

Authors: Ratchaneewan Salao, Steven W. Edwards, Kiatichai Faksri, Kanin Salao

Abstract:

Background: A two-dose regimen of COVID-19 vaccination (inactivated whole virion SARS-CoV-2 and adenoviral vector) has been widely used. Side effects are very low, but several adverse effects have been reported. Methods: A 40-year-old female patient, with a previous history of thyroid goitre, developed severe neck pain, headache, nausea and fatigue 7-days after receiving second vaccination with Vaxzevria® (Oxford-AstraZeneca). Clinical and laboratory findings, including thyroid function tests and ultrasound of thyroid glands, were performed. Results: Her left thyroid gland was multinodular enlarged, and severely tender on palpation. She had difficulty in swallowing and had tachycardia but no signs of hyperthyroidism. Laboratory results supported a diagnosis of subacute thyroiditis. She was prescribed NSAID (Ibuprofen 400 mg) and dexamethasone for 3-days and her symptoms resolved. Conclusions: Although this is an extremely rare event, physicians may encounter more cases of this condition due to the extensive vaccination program using this combination of vaccines.

Keywords: SARS-CoV-2, adenoviral vector vaccines, vaccination, subacute thyroiditis

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1695 Environmental Monitoring by Using Unmanned Aerial Vehicle (UAV) Images and Spatial Data: A Case Study of Mineral Exploitation in Brazilian Federal District, Brazil

Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

Abstract:

Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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1694 Topographic Coast Monitoring Using UAV Photogrammetry: A Case Study in Port of Veracruz Expansion Project

Authors: Francisco Liaño-Carrera, Jorge Enrique Baños-Illana, Arturo Gómez-Barrero, José Isaac Ramírez-Macías, Erik Omar Paredes-JuáRez, David Salas-Monreal, Mayra Lorena Riveron-Enzastiga

Abstract:

Topographical changes in coastal areas are usually assessed with airborne LIDAR and conventional photogrammetry. In recent times Unmanned Aerial Vehicles (UAV) have been used several in photogrammetric applications including coastline evolution. However, its use goes further by using the points cloud associated to generate beach Digital Elevation Models (DEM). We present a methodology for monitoring coastal topographic changes along a 50 km coastline in Veracruz, Mexico using high-resolution images (less than 10 cm ground resolution) and dense points cloud captured with an UAV. This monitoring develops in the context of the port of Veracruz expansion project which construction began in 2015 and intends to characterize coast evolution and prevent and mitigate project impacts on coastal environments. The monitoring began with a historical coastline reconstruction since 1979 to 2015 using aerial photography and Landsat imagery. We could define some patterns: the northern part of the study area showed accretion while the southern part of the study area showed erosion. Since the study area is located off the port of Veracruz, a touristic and economical Mexican urban city, where coastal development structures have been built since 1979 in a continuous way, the local beaches of the touristic area are been refilled constantly. Those areas were not described as accretion since every month sand-filled trucks refill the sand beaches located in front of the hotel area. The construction of marinas and the comitial port of Veracruz, the old and the new expansion were made in the erosion part of the area. Northward from the City of Veracruz the beaches were described as accretion areas while southward from the city, the beaches were described as erosion areas. One of the problems is the expansion of the new development in the southern area of the city using the beach view as an incentive to buy front beach houses. We assessed coastal changes between seasons using high-resolution images and also points clouds during 2016 and preliminary results confirm that UAVs can be used in permanent coast monitoring programs with excellent performance and detail.

Keywords: digital elevation model, high-resolution images, topographic coast monitoring, unmanned aerial vehicle

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1693 Particle Swarm Optimization Algorithm vs. Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform

Authors: Omaima N. Ahmad AL-Allaf

Abstract:

Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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1692 Magnetic Resonance Imaging for Assessment of the Quadriceps Tendon Cross-Sectional Area as an Adjunctive Diagnostic Parameter in Patients with Patellofemoral Pain Syndrome

Authors: Jae Ni Jang, SoYoon Park, Sukhee Park, Yumin Song, Jae Won Kim, Keum Nae Kang, Young Uk Kim

Abstract:

Objectives: Patellofemoral pain syndrome (PFPS) is a common clinical condition characterized by anterior knee pain. Here, we investigated the quadriceps tendon cross-sectional area (QTCSA) as a novel predictor for the diagnosis of PFPS. By examining the association between the QTCSA and PFPS, we aimed to provide a more valuable diagnostic parameter and more equivocal assessment of the diagnostic potential of PFPS by comparing the QTCSA with the quadriceps tendon thickness (QTT), a traditional measure of quadriceps tendon hypertrophy. Patients and Methods: This retrospective study included 30 patients with PFPS and 30 healthy participants who underwent knee magnetic resonance imaging. T1-weighted turbo spin echo transverse magnetic resonance images were obtained. The QTCSA was measured on the axial-angled phases of the images by drawing outlines, and the QTT was measured at the most hypertrophied quadriceps tendon. Results: The average QTT and QTCSA for patients with PFPS (6.33±0.80 mm and 155.77±36.60 mm², respectively) were significantly greater than those for healthy participants (5.77±0.36 mm and 111.90±24.10 mm2, respectively; both P<0.001). We used a receiver operating characteristic curve to confirm the sensitivities and specificities for both the QTT and QTCSA as predictors of PFPS. The optimal diagnostic cutoff value for QTT was 5.98 mm, with a sensitivity of 66.7%, a specificity of 70.0%, and an area under the curve of 0.75 (0.62–0.88). The optimal diagnostic cutoff value for QTCSA was 121.04 mm², with a sensitivity of 73.3%, a specificity of 70.0%, and an area under the curve of 0.83 (0.74–0.93). Conclusion: The QTCSA was found to be a more reliable diagnostic indicator for PFPS than QTT.

Keywords: patellofemoral pain syndrome, quadriceps muscle, hypertrophy, magnetic resonance imaging

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1691 A U-Net Based Architecture for Fast and Accurate Diagram Extraction

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

Abstract:

In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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1690 Optimization of Ultrasonic Assisted Extraction of Antioxidants and Phenolic Compounds from Coleus Using Response Surface Methodology

Authors: Reihaneh Ahmadzadeh Ghavidel

Abstract:

Free radicals such as reactive oxygen species (ROS) have detrimental effects on human health through several mechanisms. On the other hand, antioxidant molecules reduce free radical generation in biologic systems. Synthetic antioxidants, which are used in food industry, have also negative impact on human health. Therefore recognition of natural antioxidants such as anthocyanins can solve these problems simultaneously. Coleus (Solenostemon scutellarioides) with red leaves is a rich source of anthocyanins compounds. In this study we evaluated the effect of time (10, 20 and 30 min) and temperature (40, 50 and 60° C) on optimization of anthocyanin extraction using surface response method. In addition, the study was aimed to determine maximum extraction for anthocyanin from coleus plant using ultrasound method. The results indicated that the optimum conditions for extraction were 39.84 min at 69.25° C. At this point, total compounds were achieved 3.7451 mg 100 ml⁻¹. Furthermore, under optimum conditions, anthocyanin concentration, extraction efficiency, ferric reducing ability, total phenolic compounds and EC50 were registered 3.221931, 6.692765, 223.062, 3355.605 and 2.614045, respectively.

Keywords: anthocyanin, antioxidant, coleus, extraction, sonication

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1689 Connecting MRI Physics to Glioma Microenvironment: Comparing Simulated T2-Weighted MRI Models of Fixed and Expanding Extracellular Space

Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

Abstract:

Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

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1688 Modeling Breathable Particulate Matter Concentrations over Mexico City Retrieved from Landsat 8 Satellite Imagery

Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa

Abstract:

In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air quality, modeling pollution, particulate matter, remote sensing

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1687 A Survey of Skin Cancer Detection and Classification from Skin Lesion Images Using Deep Learning

Authors: Joseph George, Anne Kotteswara Roa

Abstract:

Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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1686 Fully Automated Methods for the Detection and Segmentation of Mitochondria in Microscopy Images

Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

Abstract:

The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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1685 Grisotti Flap as Treatment for Central Tumors of the Breast

Authors: R. Pardo, P. Menendez, MA Gil-Olarte, S. Sanchez, E. García, R. Quintana, J. Martín

Abstract:

Introduction : Within oncoplastic breast techniques there is increased interest in immediate partial breast reconstruction. The volume resected is greater than that of conventional conservative techniques. Central tumours of the breast have classically been treated with a mastectomy with regard to oncological safety and cosmetic secondary effects after wide central resection of the nipple and breast tissue beneath. Oncological results for central quadrantectomy have a recurrence level, disease- free period and survival identical to mastectomy. Grissoti flap is an oncoplastic surgical technique that allows the surgeon to perform a safe central quadrantectomy with excellent cosmetic results. Material and methods: The Grissoti flap is a glandular cutaneous advancement rotation flap that can fill the defect in the central portion of the excised breast. If the inferior border is affected by tumour and further surgery is decided upon at the Multidisciplinary Team Meeting, it will be necessary to perform a mastectomy. All patients with a Grisotti flap undergoing surgery since 2009 were reviewed obtaining the following data: age, hystopathological diagnosis, size, operating time, volume of tissue resected, postoperative admission time, re-excisions due to positive margins affected by tumour, wound dehiscence, complications and recurrence. Analysis and results of sentinel node biopsy were also obtained. Results: 12 patients underwent surgery between 2009-2015. The mean age was 54 years (34-67) . All had a preoperative diagnosis of ductal infiltrative carcinoma of less than 2 cm,. Diagnosis was made with Ultrasound, Mamography or both . Magnetic resonance was used in 5 cases. No patients had preoperative positive axilla after ultrasound exploration. Mean operating time was 104 minutes (84-130). Postoperative stay was 24 hours. Mean volume resected was 159 cc (70-286). In one patient the surgical border was affected by tumour and a further procedure with resection of the affected border was performed as ambulatory surgery. The sentinel node biopsy was positive for micrometastasis in only two cases. In one case lymphadenectomy was performed in 2009. In the other, treated in 2015, no lymphadenectomy was performed as the patient had a favourable histopathological prognosis and the multidisciplinary team meeting agreed that lymphadenectomy was not required. No recurrence has been diagnosed in any of the patients who underwent surgery and they are all disease free at present. Conclusions: Conservative surgery for retroareolar central tumours of the breast results in good local control of the disease with free surgical borders, including resection of the nipple areola complex and pectoral major muscle fascia. Reconstructive surgery with the inferior Grissoti flap adequately fills the defect after central quadrantectomy with creation of a new cutaneous disc where a new nipple areola complex is reconstructed with a local flap or micropigmentation. This avoids the need for contralateral symmetrization. Sentinel Node biopsy can be performed without added morbidity. When feasible, the Grissoti flap will avoid skin-sparing mastectomy for central breast tumours that will require the use of an expander, prosthesis or myocutaneous flap, with all the complications of a more complex operation.

Keywords: Grisotti flap, oncoplastic surgery, central tumours, breast

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1684 Omni-Modeler: Dynamic Learning for Pedestrian Redetection

Authors: Michael Karnes, Alper Yilmaz

Abstract:

This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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1683 The Impact of Ultrasonic Field to Increase the Biodegradability of Leachate from The Landfill

Authors: Kwarciak-Kozlowska A., Slawik-Dembiczak L., Galwa-Widera M.

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Complex and variable during operation of the landfill leachate composition prevents the use of a single universal method of their purification. Due to the presence of difficult biodegradable these substances in the wastewater, cleaning of them often requires the use of biological methods (activated sludge or anaerobic digestion), also often supporting by physicochemical processes. Currently, more attention is paid to the development of unconventional methods of disposal of sewage m.in ultleniania advanced methods including the use of ultrasonic waves. It was assumed that the ultrasonic waves induce change in the structure of organic compounds and contribute to the acceleration of biodegradability, including refractive substances in the leachate, so that will increase the effectiveness of their treatment in biological processes. We observed a marked increase in BOD leachate when subjected to the action of utradźwięowego. Ratio BOD / COD was 27% higher compared to the value of this ratio for leachate nienadźwiękawianych. It was found that the process of sonification leachate clearly influenced the formation and release of aliphatic compounds. These changes suggest a possible violation of the chemical structure of organic compounds in the leachate thereby give compounds of the chemical structure more susceptible to biodegradation.

Keywords: IR spectra, landfill leachate, organic pollutants, ultrasound

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1682 Lung HRCT Pattern Classification for Cystic Fibrosis Using a Convolutional Neural Network

Authors: Parisa Mansour

Abstract:

Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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1681 Effect of Incorporation of Seaweed Extract in Gelatin Based Film on Physic-Chemical and Bioactive Properties of Film

Authors: Shekhar U. Kadam, S. K. Pankaj, Brijesh K. Tiwari, P. J. Cullen, Colm P. O’Donnell

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Brown seaweed L. hyperborea is a rich source of phenolic compounds with antioxidant and antimicrobial properties. The aim of this work was to study the effect of incorporation of L. hyperborea extract to bovine gelatin film on the physicochemical and antioxidant properties of film. Films with fraction of 25% by weight of bovine gelatin sample were cast with addition of glycerol as a plasticizer. The total phenolic content and antioxidant activity of the films showed higher levels with addition of seaweed extract. Also film appearance properties such as film thickness, color and light transparency were evaluated. Film appearance was slightly modified whereas microstructure of films showed rough patches at 50% level of extract in the film. Hydrophilicity and glass transition temperature of the films also increased with increased level of seaweed extract. It was found that seaweed extract can be incorporated within gelatin and casein for development of biofunctional films.

Keywords: Laminaria hyperborea, ultrasound, seaweed extract, bovine gelatin film, antioxidant, phenolic compounds

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1680 COVID-19 Detection from Computed Tomography Images Using UNet Segmentation, Region Extraction, and Classification Pipeline

Authors: Kenan Morani, Esra Kaya Ayana

Abstract:

This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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1679 Aspects and Studies of Fractal Geometry in Automatic Breast Cancer Detection

Authors: Mrinal Kanti Bhowmik, Kakali Das Jr., Barin Kumar De, Debotosh Bhattacharjee

Abstract:

Breast cancer is the most common cancer and a leading cause of death for women in the 35 to 55 age group. Early detection of breast cancer can decrease the mortality rate of breast cancer. Mammography is considered as a ‘Gold Standard’ for breast cancer detection and a very popular modality, presently used for breast cancer screening and detection. The screening of digital mammograms often leads to over diagnosis and a consequence to unnecessary traumatic & painful biopsies. For that reason recent studies involving the use of thermal imaging as a screening technique have generated a growing interest especially in cases where the mammography is limited, as in young patients who have dense breast tissue. Tumor is a significant sign of breast cancer in both mammography and thermography. The tumors are complex in structure and they also exhibit a different statistical and textural features compared to the breast background tissue. Fractal geometry is a geometry which is used to describe this type of complex structure as per their main characteristic, where traditional Euclidean geometry fails. Over the last few years, fractal geometrics have been applied mostly in many medical image (1D, 2D, or 3D) analysis applications. In breast cancer detection using digital mammogram images, also it plays a significant role. Fractal is also used in thermography for early detection of the masses using the thermal texture. This paper presents an overview of the recent aspects and initiatives of fractals in breast cancer detection in both mammography and thermography. The scope of fractal geometry in automatic breast cancer detection using digital mammogram and thermogram images are analysed, which forms a foundation for further study on application of fractal geometry in medical imaging for improving the efficiency of automatic detection.

Keywords: fractal, tumor, thermography, mammography

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1678 Evaluation of the Urban Landscape Structures and Dynamics of Hawassa City, Using Satellite Images and Spatial Metrics Approaches, Ethiopia

Authors: Berhanu Terfa, Nengcheng C.

Abstract:

The study deals with the analysis of urban expansion and land transformation of Hawass City using remote sensing data and landscape metrics during last three decades (1987–2017). Remote sensing data from Various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used to examine the urban expansion, growth types, and spatial isolation within the urban landscape to develop an understanding the trends of built-up growth in Hawassa City, Ethiopia. Landscape metrics and built-up density were employed to analyze the pattern, process and overall growth status. The area under investigation was divided into concentric circles with a consecutive circle of 1 km incremental radius from the central pixel (Central Business District) for analysis. The result exhibited that the built-up area had increased by 541.32% between 1987 and 2017and an extension growth types (more than 67 %) was observed. The major growth took place in north-west direction followed by north direction in haphazard manner during 1987–1995 period, whereas predominant built-up development was observed in south and southwest direction during 1995–2017 period. Land scape metrics result revealed that the of urban patches density, total edge and edge density increased, while mean nearest neighbors’ distance decreased showing the tendency of sprawl.

Keywords: landscape metrics, spatial patterns, remote sensing, multi-temporal, urban sprawl

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1677 Enhanced Acquisition Time of a Quantum Holography Scheme within a Nonlinear Interferometer

Authors: Sergio Tovar-Pérez, Sebastian Töpfer, Markus Gräfe

Abstract:

The work proposes a technique that decreases the detection acquisition time of quantum holography schemes down to one-third; this allows the possibility to image moving objects. Since its invention, quantum holography with undetected photon schemes has gained interest in the scientific community. This is mainly due to its ability to tailor the detected wavelengths according to the needs of the scheme implementation. Yet this wavelength flexibility grants the scheme a wide range of possible applications; an important matter was yet to be addressed. Since the scheme uses digital phase-shifting techniques to retrieve the information of the object out of the interference pattern, it is necessary to acquire a set of at least four images of the interference pattern along with well-defined phase steps to recover the full object information. Hence, the imaging method requires larger acquisition times to produce well-resolved images. As a consequence, the measurement of moving objects remains out of the reach of the imaging scheme. This work presents the use and implementation of a spatial light modulator along with a digital holographic technique called quasi-parallel phase-shifting. This technique uses the spatial light modulator to build a structured phase image consisting of a chessboard pattern containing the different phase steps for digitally calculating the object information. Depending on the reduction in the number of needed frames, the acquisition time reduces by a significant factor. This technique opens the door to the implementation of the scheme for moving objects. In particular, the application of this scheme in imaging alive specimens comes one step closer.

Keywords: quasi-parallel phase shifting, quantum imaging, quantum holography, quantum metrology

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1676 Digitizing Masterpieces in Italian Museums: Techniques, Challenges and Consequences from Giotto to Caravaggio

Authors: Ginevra Addis

Abstract:

The possibility of reproducing physical artifacts in a digital format is one of the opportunities offered by the technological advancements in information and communication most frequently promoted by museums. Indeed, the study and conservation of our cultural heritage have seen significant advancement due to the three-dimensional acquisition and modeling technology. A variety of laser scanning systems has been developed, based either on optical triangulation or on time-of-flight measurement, capable of producing digital 3D images of complex structures with high resolution and accuracy. It is necessary, however, to explore the challenges and opportunities that this practice brings within museums. The purpose of this paper is to understand what change is introduced by digital techniques in those museums that are hosting digital masterpieces. The methodology used will investigate three distinguished Italian exhibitions, related to the territory of Milan, trying to analyze the following issues about museum practices: 1) how digitizing art masterpieces increases the number of visitors; 2) what the need that calls for the digitization of artworks; 3) which techniques are most used; 4) what the setting is; 5) the consequences of a non-publication of hard copies of catalogues; 6) envision of these practices in the future. Findings will show how interconnection plays an important role in rebuilding a collection spread all over the world. Secondly how digital artwork duplication and extension of reality entail new forms of accessibility. Thirdly, that collection and preservation through digitization of images have both a social and educational mission. Fourthly, that convergence of the properties of different media (such as web, radio) is key to encourage people to get actively involved in digital exhibitions. The present analysis will suggest further research that should create museum models and interaction spaces that act as catalysts for innovation.

Keywords: digital masterpieces, education, interconnection, Italian museums, preservation

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1675 A Deleuzean Feminist Analysis of the Everyday, Gendered Performances of Teen Femininity: A Case Study on Snaps and Selfies in East London

Authors: Christine Redmond

Abstract:

This paper contributes to research on gendered, digital identities by exploring how selfies offer scope for disrupting and moving through gendered and racial ideals of feminine beauty. The selfie involves self-presentation, filters, captions, hashtags, online publishing, likes and more, constituting the relationship between subjectivity, practice and social use of selfies a complex process. Employing qualitative research methods on youth selfies in the UK, the author investigates interdisciplinary entangling between studies of social media and fields within gender, media and cultural studies, providing a material discursive treatment of the selfie as an embodied practice. Drawing on data collected from focus groups with teenage girls in East London, the study explores how girls experience and relate to selfies and snaps in their everyday lives. The author’s Deleuzean feminist approach suggests that bodies and selfies are not individual, disembodied entities between which there is a mediating inter-action. Instead, bodies and selfies are positioned as entangled to a point where it becomes unclear as to where a selfie ends and a body begins. Recognising selfies not just as images but as material and social assemblages opens up possibilities for unpacking the selfie in ways that move beyond the representational model in some studies of socially mediated digital images. The study reveals how the selfie functions to enable moments of empowerment within limiting, dominant ideologies of Euro-centrism, patriarchy and heteronormativity.

Keywords: affect theory, femininity, gender, heteronormativity, photography, selfie, snapchat

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1674 Drape Simulation by Commercial Software and Subjective Assessment of Virtual Drape

Authors: Evrim Buyukaslan, Simona Jevsnik, Fatma Kalaoglu

Abstract:

Simulation of fabrics is more difficult than any other simulation due to complex mechanics of fabrics. Most of the virtual garment simulation software use mass-spring model and incorporate fabric mechanics into simulation models. The accuracy and fidelity of these virtual garment simulation software is a question mark. Drape is a subjective phenomenon and evaluation of drape has been studied since 1950’s. On the other hand, fabric and garment simulation is relatively new. Understanding drape perception of subjects when looking at fabric simulations is critical as virtual try-on becomes more of an issue by enhanced online apparel sales. Projected future of online apparel retailing is that users may view their avatars and try-on the garment on their avatars in the virtual environment. It is a well-known fact that users will not be eager to accept this innovative technology unless it is realistic enough. Therefore, it is essential to understand what users see when they are displaying fabrics in a virtual environment. Are they able to distinguish the differences between various fabrics in virtual environment? The purpose of this study is to investigate human perception when looking at a virtual fabric and determine the most visually noticeable drape parameter. To this end, five different fabrics are mechanically tested, and their drape simulations are generated by commercial garment simulation software (Optitex®). The simulation images are processed by an image analysis software to calculate drape parameters namely; drape coefficient, node severity, and peak angles. A questionnaire is developed to evaluate drape properties subjectively in a virtual environment. Drape simulation images are shown to 27 subjects and asked to rank the samples according to their questioned drape property. The answers are compared to the calculated drape parameters. The results show that subjects are quite sensitive to drape coefficient changes while they are not very sensitive to changes in node dimensions and node distributions.

Keywords: drape simulation, drape evaluation, fabric mechanics, virtual fabric

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1673 The Event of Extreme Precipitation Occurred in the Metropolitan Mesoregion of the Capital of Para

Authors: Natasha Correa Vitória Bandeira, Lais Cordeiro Soares, Claudineia Brazil, Luciane Teresa Salvi

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The intense rain event that occurred between February 16 and 18, 2018, in the city of Barcarena in Pará, located in the North region of Brazil, demonstrates the importance of analyzing this type of event. The metropolitan mesoregion of Belem was severely punished by rains much above the averages normally expected for that time of year; this phenomenon affected, in addition to the capital, the municipalities of Barcarena, Murucupi and Muruçambá. Resulting in a great flood in the rivers of the region, whose basins were affected with great intensity of precipitation, causing concern for the local population because in this region, there are located companies that accumulate ore tailings, and in this specific case, the dam of any of these companies, leaching the ore to the water bodies of the Murucupi River Basin. This article aims to characterize this phenomenon through a special analysis of the distribution of rainfall, using data from atmospheric soundings, satellite images, radar images and data from the GPCP (Global Precipitation Climatology Project), in addition to rainfall stations located in the study region. The results of the work demonstrated a dissociation between the data measured in the meteorological stations and the other forms of analysis of this extreme event. Monitoring carried out solely on the basis of data from pluviometric stations is not sufficient for monitoring and/or diagnosing extreme weather events, and investment by the competent bodies is important to install a larger network of pluviometric stations sufficient to meet the demand in a given region.

Keywords: extreme precipitation, great flood, GPCP, ore dam

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1672 Cognitive Linguistic Features Underlying Spelling Development in a Second Language: A Case Study of L2 Spellers in South Africa

Authors: A. Van Staden, A. Tolmie, E. Vorster

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Research confirms the multifaceted nature of spelling development and underscores the importance of both cognitive and linguistic skills that affect sound spelling development such as working and long-term memory, phonological and orthographic awareness, mental orthographic images, semantic knowledge and morphological awareness. This has clear implications for many South African English second language spellers (L2) who attempt to become proficient spellers. Since English has an opaque orthography, with irregular spelling patterns and insufficient sound/grapheme correspondences, L2 spellers can neither rely, nor draw on the phonological awareness skills of their first language (for example Sesotho and many other African languages), to assist them to spell the majority of English words. Epistemologically, this research is informed by social constructivism. In addition the researchers also hypothesized that the principles of the Overlapping Waves Theory was an appropriate lens through which to investigate whether L2 spellers could significantly improve their spelling skills via the implementation of an alternative route to spelling development, namely the orthographic route, and more specifically via the application of visual imagery. Post-test results confirmed the results of previous research that argues for the interactive nature of different cognitive and linguistic systems such as working memory and its subsystems and long-term memory, as learners were systematically guided to store visual orthographic images of words in their long-term lexicons. Moreover, the results have shown that L2 spellers in the experimental group (n = 9) significantly outperformed L2 spellers (n = 9) in the control group whose intervention involved phonological awareness (and coding) including the teaching of spelling rules. Consequently, L2 learners in the experimental group significantly improved in all the post-test measures included in this investigation, namely the four sub-tests of short-term memory; as well as two spelling measures (i.e. diagnostic and standardized measures). Against this background, the findings of this study look promising and have shown that, within a social-constructivist learning environment, learners can be systematically guided to apply higher-order thinking processes such as visual imagery to successfully store and retrieve mental images of spelling words from their output lexicons. Moreover, results from the present study could play an important role in directing research into this under-researched aspect of L2 literacy development within the South African education context.

Keywords: English second language spellers, phonological and orthographic coding, social constructivism, visual imagery as spelling strategy

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1671 Upgrading of Problem-Based Learning with Educational Multimedia to the Undergraduate Students

Authors: Sharifa Alduraibi, Abir El Sadik, Ahmed Elzainy, Alaa Alduraibi, Ahmed Alsolai

Abstract:

Introduction: Problem-based learning (PBL) is an active student-centered educational modality, influenced by the students' interest that required continuous motivation to improve their engagement. The new era of professional information technology facilitated the utilization of educational multimedia, such as videos, soundtracks, and photographs promoting students' learning. The aim of the present study was to introduce multimedia-enriched PBL scenarios for the first time in college of medicine, Qassim University, as an incentive for better students' engagement. In addition, students' performance and satisfaction were evaluated. Methodology: Two multimedia-enhanced PBL scenarios were implemented to the third years' students in the urinary system block. Radiological images, plain CT scan, and X-ray of the abdomen and renal nuclear scan correlated with their pathological gross photographs were added to the scenarios. One week before the first sessions, pre-recorded orientation videos for PBL tutors were submitted to clarify the multimedia incorporated in the scenarios. Other two traditional PBL scenarios devoid of multimedia demonstrating the pathological and radiological findings were designed. Results and Discussion: Comparison between the formative assessments' results by the end of the two PBL modalities was done. It revealed significant increase in students' engagement, critical thinking and practical reasoning skills during the multimedia-enhanced sessions. Students' perception survey showed great satisfaction with the new strategy. Conclusion: It could be concluded from the current work that multimedia created technology-based teaching strategy inspiring the student for self-directed thinking and promoting students' overall achievement.

Keywords: multimedia, pathology and radiology images, problem-based learning, videos

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1670 Nature Manifestations: An Archetypal Analysis of Selected Nightwish Songs

Authors: Suzanne Strauss, Leandi Steenkamp

Abstract:

The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

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