Search results for: medical resonance (MR) images

Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel

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Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.

Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization

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Authors: Sarita Magu, Deepak Singh

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Study Design: This prospective study was conducted at the department of Radio Diagnosis, at Pt B.D. Sharma PGIMS, Rohtak in 57 patients of spine injury on radiographs or radiographically normal patients with neurological deficits presenting within 72 hours of injury. Aims: Evaluation of the role of Magnetic Resonance Imaging (MRI) in Spinal Trauma Patients and to compare MRI findings with clinical profile and neurological status of the patient and to correlate the MRI findings with neurological recovery of the patient and predict the outcome. Material and Methods: Neurological status of patients was assessed at the time of admission and discharge in all the patients and at long term interval of six months to one year in 27 patients as per American spine injury association classification (ASIA). On MRI cord injury was categorized into cord hemorrhage, cord contusion, cord edema only, and normal cord. Quantitative assessment of injury on MRI was done using mean canal compromise (MCC), mean spinal cord compression (MSCC) and lesion length. Neurological status at admission and neurological recovery at discharge and long term follow up was compared with various qualitative cord findings and quantitative parameters on MRI. Results: Cord edema and normal cord was associated with favorable neurological outcome. Cord contusion show lesser neurological recovery as compared to cord edema. Cord hemorrhage was associated with worst neurological status at admission and poor neurological recovery. Mean MCC, MSCC, and lesion length values were higher in patients presenting with ASIA A grade injury and showed decreasing trends towards ASIA E grade injury. Patients showing neurological recovery over the period of hospital stay and long term follow up had lower mean MCC, MSCC, and lesion length as compared to patients showing no neurological recovery. The data was statistically significant with p value <.05. Conclusion: Cord hemorrhage and higher MCC, MSCC and lesion length has poor prognostic value in spine injury patients.

Keywords: spine injury, cord hemorrhage, cord contusion, MCC, MSCC, lesion length, ASIA grading

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Authors: Rozo D. Juan Felipe, Ramírez L. Leonardo Juan, Puerta A. Gabriel Alberto

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The telemedicine services require correct computing resource management to guarantee productivity and efficiency for medical and non-medical staff. The aim of this study was to examine web management strategies to ensure the availability of resources and services in telemedicine so as to provide medical information management with an accessible strategy. In addition, to evaluate the quality-of-service parameters, the followings were measured: delays, throughput, jitter, latency, available bandwidth, percent of access and denial of services based of web management performance map with profiles permissions and database management. Through 24 different test scenarios, the results show 100% in availability of medical information, in relation to access of medical staff to web services, and quality of service (QoS) of 99% because of network delay and performance of computer network. The findings of this study suggest that the proposed strategy of web management is an ideal solution to guarantee the availability, reliability, and accessibility of medical information. Finally, this strategy offers seven user profile used at telemedicine center of Bogota-Colombia keeping QoS parameters suitable to telemedicine services.

Keywords: availability, medical information, QoS, strategy, telemedicine

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Authors: Faidon Kyriakou, William Dempster, David Nash

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Abdominal Aortic Aneurysm (AAA) is a major life-threatening pathology for which modern approaches reduce the need for open surgery through the use of stenting. The success of stenting though is sometimes jeopardized by the final position of the stent graft inside the human artery which may result in migration, endoleaks or blood flow occlusion. Herein, a finite element (FE) model of the commercial medical device AnacondaTM (Vascutek, Terumo) has been developed and validated in order to create a numerical tool able to provide useful clinical insight before the surgical procedure takes place. The AnacondaTM device consists of a series of NiTi rings sewn onto woven polyester fabric, a structure that despite its column stiffness is flexible enough to be used in very tortuous geometries. For the purposes of this study, a FE model of the device was built in Abaqus® (version 6.13-2) with the combination of beam, shell and surface elements; the choice of these building blocks was made to keep the computational cost to a minimum. The validation of the numerical model was performed by comparing the deployed position of a full stent graft device inside a constructed AAA with a duplicate set-up in Abaqus®. Specifically, an AAA geometry was built in CAD software and included regions of both high and low tortuosity. Subsequently, the CAD model was 3D printed into a transparent aneurysm, and a stent was deployed in the lab following the steps of the clinical procedure. Images on the frontal and sagittal planes of the experiment allowed the comparison with the results of the numerical model. By overlapping the experimental and computational images, the mean and maximum distances between the rings of the two models were measured in the longitudinal, and the transverse direction and, a 5mm upper bound was set as a limit commonly used by clinicians when working with simulations. The two models showed very good agreement of their spatial positioning, especially in the less tortuous regions. As a result, and despite the inherent uncertainties of a surgical procedure, the FE model allows confidence that the final position of the stent graft, when deployed in vivo, can also be predicted with significant accuracy. Moreover, the numerical model run in just a few hours, an encouraging result for applications in the clinical routine. In conclusion, the efficient modelling of a complicated structure which combines thin scaffolding and fabric has been demonstrated to be feasible. Furthermore, the prediction capabilities of the location of each stent ring, as well as the global shape of the graft, has been shown. This can allow surgeons to better plan their procedures and medical device manufacturers to optimize their designs. The current model can further be used as a starting point for patient specific CFD analysis.

Keywords: AAA, efficiency, finite element analysis, stent deployment

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Authors: Q. Ni, J. A. Serna, D. Holland, X. Wang

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The objective of this study is to develop Nuclear Magnetic Resonance (NMR) techniques to enhance bone related research applied on normal and disuse (Biglycan knockout) mice bone in vitro by using both low-field and high-field NMR simultaneously. It is known that the total amplitude of T₂ relaxation envelopes, measured by the Carr-Purcell-Meiboom-Gill NMR spin echo train (CPMG), is a representation of the liquid phase inside the pores. Therefore, the NMR CPMG magnetization amplitude can be transferred to the volume of water after calibration with the NMR signal amplitude of the known volume of the selected water. In this study, the distribution of mobile water, porosity that can be determined by using low-field (20 MHz) CPMG relaxation technique, and the pore size distributions can be determined by a computational inversion relaxation method. It is also known that the total proton intensity of magnetization from the NMR free induction decay (FID) signal is due to the water present inside the pores (mobile water), the water that has undergone hydration with the bone (bound water), and the protons in the collagen and mineral matter (solid-like protons). Therefore, the components of total mobile and bound water within bone that can be determined by low-field NMR free induction decay technique. Furthermore, the bound water in solid phase (mineral and organic constituents), especially, the dominated component of calcium hydroxyapatite (Ca₁₀(OH)₂(PO₄)₆) can be determined by using high-field (400 MHz) magic angle spinning (MAS) NMR. With MAS technique reducing NMR spectral linewidth inhomogeneous broadening and susceptibility broadening of liquid-solid mix, in particular, we can conduct further research into the ¹H and ³¹P elements and environments of bone materials to identify the locations of bound water such as OH- group within minerals and bone architecture. We hypothesize that with low-field and high-field magic angle spinning NMR can provide a more complete interpretation of water distribution, particularly, in bound water, and these data are important to access bone quality and predict the mechanical behavior of bone.

Keywords: bone, mice bone, NMR, water in bone

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Authors: Yi Jen Wang, Yu Ju Chen

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Background: Heart rate variability (HRV) biofeedback can promote autonomic nervous function, sleep quality and reduce psychological stress. In HRV biofeedback training, it is hoped that through the guidance of machine video or audio, the patient can breathe slowly according to his own heart rate changes so that the heart and lungs can achieve resonance, thereby promoting the related effects of autonomic nerve function; while, it is also pointed out that if slow breathing of 6 times per minute can also guide the case to achieve the effect of cardiopulmonary resonance. However, there is no relevant research to explore the comparison of the effectiveness of cardiopulmonary resonance by using video or audio HRV biofeedback training and metronome-guided slow breathing. Purpose: To compare the promotion of autonomic nervous function performance between using HRV biofeedback and slow breathing guided by a metronome. Method: This research is a kind of experimental design with convenient sampling; the cases are randomly divided into the heart rate variability biofeedback training group and the slow breathing training group. The HRV biofeedback training group will conduct HRV biofeedback training in a four-week laboratory and use the home training device for autonomous training; while the slow breathing training group will conduct slow breathing training in the four-week laboratory using the mobile phone APP breathing metronome to guide the slow breathing training, and use the mobile phone APP for autonomous training at home. After two groups were enrolled and four weeks after the intervention, the autonomic nervous function-related performance was repeatedly measured. Using the chi-square test, student’s t-test and other statistical methods to analyze the results, and use p <0.05 as the basis for statistical significance. Results: A total of 27 subjects were included in the analysis. After four weeks of training, the HRV biofeedback training group showed significant improvement in the HRV indexes (SDNN, RMSSD, HF, TP) and sleep quality. Although the stress index also decreased, it did not reach statistical significance; the slow breathing training group was not statistically significant after four weeks of training, only sleep quality improved significantly, while the HRV indexes (SDNN, RMSSD, TP) all increased. Although HF and stress indexes decreased, they were not statistically significant. Comparing the difference between the two groups after training, it was found that the HF index improved significantly and reached statistical significance in the HRV biofeedback training group. Although the sleep quality of the two groups improved, it did not reach that level in a statistically significant difference. Conclusion: HRV biofeedback training is more effective in promoting autonomic nervous function than slow breathing training, but the effects of reducing stress and promoting sleep quality need to be explored after increasing the number of samples. The results of this study can provide a reference for clinical or community health promotion. In the future, it can also be further designed to integrate heart rate variability biological feedback training into the development of AI artificial intelligence wearable devices, which can make it more convenient for people to train independently and get effective feedback in time.

Keywords: autonomic nervous function, HRV biofeedback, heart rate variability, slow breathing

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Authors: Uliana N. Tumanova, Sergey M. Voevodin, Veronica A. Sinitsyna, Alexandr I. Shchegolev

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An important part of forensic and autopsy research in perinatology is the answer to the question of life and stillbirth. Postmortem magnetic resonance imaging (MRI) is an objective non-invasive research method that allows to store data for a long time and not to exhume the body to clarify the diagnosis. The purpose of the research is to study the possibilities of a postmortem MRI to determine the stillbirth and death of a newborn who had spontaneous breathing and died on the first day after birth. MRI and morphological data of a study of 23 stillborn bodies, prenatally dead at a gestational age of 22-39 weeks (Group I) and the bodies of 16 newborns who died from 2 to 24 hours after birth (Group II) were compared. Before the autopsy, postmortem MRI was performed on the Siemens Magnetom Verio 3T device in the supine position of the body. The control group for MRI studies consisted of 7 live newborns without lung disease (Group III). On T2WI in the sagittal projection was measured MR-signal intensity (SI) in the lung tissue (L) and shoulder muscle (M). During the autopsy, a pulmonary swimming test was evaluated, and macro- and microscopic studies were performed. According to the postmortem MRI, the highest values of mean SI of the lung (430 ± 27.99) and of the muscle (405.5 ± 38.62) on T2WI were detected in group I and exceeded the corresponding value of group II by 2.7 times. The lowest values were found in the control group - 77.9 ± 12.34 and 119.7 ± 6.3, respectively. In the group II, the lung SI was 1.6 times higher than the muscle SI, whereas in the group I and in the control group, the muscle SI was 2.1 times and 1.8 times larger than the lung. On the basis of clinical and morphological data, we calculated the formula for determining the breathing index (BI) during postmortem MRI: BI = SIL x SIM / 100. The mean value of BI in the group I (1801.14 ± 241.6) (values ranged from 756 to 3744) significantly higher than the corresponding average value of BI in the group II (455.89 ± 137.32, p < 0.05) (305-638.4). In the control group, the mean BI value was 91.75 ± 13.3 (values ranged from 53 to 154). The BI with the results of pulmonary swimming tests and microscopic examination of the lungs were compared. The boundary value of BI for the differential diagnosis of stillborn and newborn death was 700. Using the postmortem MRI allows to differentiate the stillborn with the death of the breathing newborn.

Keywords: lung, newborn, postmortem MRI, stillborn

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Qian Pei, Hengjian Tong, Weitao Chen, Hai Wang, Yanrong Feng

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Horizontal parallax is the foundation of stereoscopic viewing. However, the human eye will feel uncomfortable and it will occur diplopia if horizontal parallax is larger than eye separation. Therefore, we need to do parallax refining before conducting stereoscopic observation. Although some scholars have been devoted to online remote sensing refining, the main work of image refining is completed on the server side. There will be a significant delay when multiple users access the server at the same time. The emergence of HTML5 technology in recent years makes it possible to develop rich browser web application. Authors complete the image parallax refining on the browser side based on HTML5, while server side only need to transfer image data and parallax file to browser side according to the browser’s request. In this way, we can greatly reduce the server CPU load and allow a large number of users to access server in parallel and respond the user’s request quickly.

Keywords: 3D remote sensing images, parallax, online refining, rich browser web application, HTML5

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Authors: Tajinder Kaur, Anu Bala

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An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

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Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

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High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

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To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

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Authors: Hamad Albadr

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Joint Commission International (JCI) accreditation process intent to improve the safety and quality of care in the international community through the provision of education, publications, consultation, and evaluation services. These standards apply to the entire organization as well as to each department, unit, or service within the organization. Medical Technology that contains both medical equipment and devices, is an essential part of health care. Appropriate management of equipment maintenance for ensuring medical technology safe, the equipment life is maximized, and the total costs are minimized. JCI medical technology evaluation and accreditation use standards, intents, and measurable elements. The paper focuses on evaluation of JCI standards for medical technology in Saudi Arabian hospitals: a Study Case of PSMMC that define the performance expectation, structures, or functions that must be in place for a hospital to be accredited by JCI through measurable elements that indicate a score during the survey process that identify the requirements for full compliance with the standard specially through Facility Management and Safety (FMS) section that require the hospital establishes and implements a program for inspecting, testing, and maintaining medical technology and documenting the results, to ensure that medical technology is available for use and functioning properly, the hospital performs and documents; an inventory of medical technology; regular inspections of medical technology; testing of medical technology according to its use and manufacturers’ requirements; and performance of preventive maintenance.

Keywords: joint commission international (JCI) accreditation, medical technology, Saudi Arabia, Saudi Arabian hospitals

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Authors: Marilyn U. Balagtas, Maria Ruth M. Regalado, Carmelina E. Barrera, Ramer V. Oxiño, Rosarito T. Suatengco, Josephine E. Tondo

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This study presents the perceptions of the students and teachers from kindergarten to tertiary level of the image of the 21st century teacher to provide basis in designing teacher development programs in Teacher Education Institutions (TEIs) in the Philippines. The highlights of the report are the personal, psychosocial, and professional images of the 21st century teacher in basic education and the teacher educators based on a survey done to 612 internal stakeholders of nine member institutions of the National Network of Normal Schools (3NS). Data were obtained through the use of a validated researcher-made instrument which allowed generation of both quantitative and qualitative descriptions of the teacher image. Through the use of descriptive statistics, the common images of the teacher were drawn, which were validated and enriched by the information drawn from the qualitative data. The study recommends a repertoire of teacher development programs to create the good image of the 21st century teachers for a better Philippines.

Keywords: teacher image, 21st century teacher, teacher education, development program

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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Authors: Monique Palma, Isabel Amaral

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This paper aims at mapping medical places in Oporto in the twentieth century in order to bring the urban history of medicine and healthcare in Portugal to a large audience, using Oporto as a case study. This analysis is consistent with the SDS's 2030 goals for policy guidance for heritage and development actors. As a result, it is critical to begin this research in order to place on the political agenda the preservation of Portuguese culture's history, memory, and heritage, particularly the medical culture, which is one of the most important drivers of civilizational development. To understand the evolution of medical care in urban history, we will conduct archive research (manuals, treatises, reports, periodic journals, newspapers, etc.) and interviews with key actors from medical institutions and medical museums. The findings of this study will be used to develop medical itineraries for inclusion in touristic agendas in Portugal and abroad, to include Portuguese medicine in global roadmaps, and to promote the preservation of the most iconic places of health care and medical heritage, as well as tools to promote social cohesion, dialogue among people, and "sense of place" globally.

Keywords: medical itineraries, history of medicine, urban history, Oporto

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Authors: L. Hamsaveni, Navya Prakash, Suresha

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Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

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Authors: Vitor S. Mendonca, Maria Luisa S. Schmidt

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The Brazilian medical profession is viewed as being error-free, so healthcare professionals who commit an error are condemned there. Medical errors occur frequently in the Brazilian healthcare system, so identifying better options for handling this issue has become of interest primarily for physicians. The purpose of this study is to better understand the tensions involved in the fear of making an error due to the harm and risk this would represent for those involved. A qualitative study was performed by means of the narratives of the lived experiences of ten acting physicians in the State of Sao Paulo. The concept and characterization of errors were discussed, together with the fear of making an error, the near misses or error in itself, how to deal with errors and what to do to avoid them. The analysis indicates an excessive pressure in the medical profession for error-free practices, with a well-established physician-patient relationship to facilitate the management of medical errors. The error occurs, but a lack of information and discussion often leads to its concealment due to fear or possible judgment by society or peers. The establishment of programs that encourage appropriate medical conduct in the event of an error requires coherent answers for humanization in Brazilian medical science. It is necessary to improve the discussion about medical errors and disseminate models of communication and notification of errors in Brazil.

Keywords: medical error, narrative, physician-patient relationship, qualitative research

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Authors: Garima Singh, Kunal Malhotra

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Objective: The expansion of telehealth has been instrumental in increasing access to medical services, especially for underserved and rural communities. In 2020, 14 million patients received virtual care through telemedicine and the global telemedicine market is expected to reach up to $185 million by 2023. It provides a platform and allows a patient to receive primary care as well as specialized care using technology and the comfort of their homes. Telemedicine was particularly useful during COVID-pandemic and the number of telehealth visits increased by 5000% during that time. It continues to serve as a significant resource for patients seeking care and to bridge the gap between the disease and the treatment. Method: As per APA (American Psychiatric Association), Telemedicine is the process of providing health care from a distance through technology. It is a subset of telemedicine, and can involve providing a range of services, including evaluations, therapy, patient education and medication management. It can involve direct interaction between a physician and the patient. It also encompasses supporting primary care providers with specialist consultation and expertise. It can also involve recording medical information (images, videos, etc.) and sending this to a distant site for later review. Results: In our organization, we are using telepsychiatry and serving 25 counties and approximately 1.4 million people. We provide multiple services, including inpatient, outpatient, crisis intervention, Rehab facility, autism services, case management, community treatment and multiple other modalities. With project ECHO (Extension for Community Healthcare Outcomes) it has been used to advise and assist primary care providers in treating mental health. It empowers primary care providers to treat patients in their own community by sharing knowledge. Conclusion: Telemedicine has shown to be a great medium in meeting patients’ needs and accessible mental health. It has been shown to improve access to care in both urban and rural settings by bringing care to a patient and reducing barriers like transportation, financial stress and resources. Telemedicine is also helping with reducing ER visits, integrating primary care and improving the continuity of care and follow-up. There has been substantial evidence and research about its effectiveness and its usage.

Keywords: telehealth, telemedicine, access to care, medical technology

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Authors: Domingo Planes Meseguer, Raffaele Danilo Esposito, Maria Del Pilar Dorado Rodriguez

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Monthly quality control checks for a Radiation Therapy Linac may be performed is a simple and efficient way once they have been standardized and protocolized. On the other hand this checks, in spite of being imperatives, require a not negligible execution times in terms of machine time and operators time. Besides it must be taken into account the amount of disposable material which may be needed together with the use of commercial software for their performing. With the aim of optimizing and standardizing mechanical-geometric checks and multi leaves collimator checks, we decided to implement a protocol which makes use of the Electronic Portal Imaging Device (EPID) available on our Linacs. The user is step by step guided by the software during the whole procedure. Acquired images are automatically analyzed by our programs all of them written using only free software.

Keywords: quality control checks, linac, radiation oncology, medical physics, free software

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Authors: Surafel Demissie, Frank Keenan, Fergal McCaffery

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Emerging medical devices are highly relying on embedded software that runs on the specific platform in real time. The development of embedded software is different from ordinary software development due to the hardware-software dependency. MDevSPICE^® has been developed to provide guidance to support such development. To increase the flexibility of this framework agile practices have been introduced. This paper outlines the challenges for embedded medical device software development and the structure of MDevSPICE^® and suggests a suitable combination of agile practices that will help to add flexibility and address corresponding challenges of embedded medical device software development.

Keywords: agile practices, challenges, embedded software, MDevSPICE®, medical device

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Authors: Yih-Chien Chen, Tse-Lung Lin

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The microwave characteristics of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ are studied to determine the feasibility of their use in the liquid sensor. The microwave characteristics of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ are determined using X-ray diffraction (XRD) patterns. The permittivity (𝜀r) of NdTi₍₀.₄₉₎Ge₀.₀₁Mo₀.₅O₄ that is sintered at 1425 ℃ for 4 h is 17.6, the unloaded quality factor (Qu×f) is 33,400 GHz, and it has a temperature coefficient at the resonance frequency (TCF) of -30.7 ppm/℃. The proposed liquid sensor is at the 5G FR1 bands.

Keywords: NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄, X-ray diffraction pattern, permittivity, Unloaded quality factor

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Authors: Theresa Slump, Paula Neumeister, Katharina Feldker, Carina Y. Heitmann, Thomas Straube

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A characteristic feature of post-traumatic stress disorder (PTSD) is the automatic processing of disorder-specific stimuli that expresses itself in intrusive symptoms such as intense physical and psychological reactions to trauma-associated stimuli. That automatic processing plays an essential role in the development and maintenance of symptoms. The aim of our study was, therefore, to investigate the behavioral and neural correlates of automatic processing of trauma-related stimuli in PTSD. Although interpersonal traumatization is a form of traumatization that often occurs, it has not yet been sufficiently studied. That is why, in our study, we focused on patients suffering from interpersonal traumatization. While previous imaging studies on PTSD mainly used faces, words, or generally negative visual stimuli, our study presented complex trauma-related and neutral visual scenes. We examined 19 female subjects suffering from PTSD and examined 19 healthy women as a control group. All subjects did a geometric comparison task while lying in a functional-magnetic-resonance-imaging (fMRI) scanner. Trauma-related scenes and neutral visual scenes that were not relevant to the task were presented while the subjects were doing the task. Regarding the behavioral level, there were not any significant differences between the task performance of the two groups. Regarding the neural level, the PTSD patients showed significant hyperactivation of the hippocampus for task-irrelevant trauma-related stimuli versus neutral stimuli when compared with healthy control subjects. Connectivity analyses revealed altered connectivity between the hippocampus and other anxiety-related areas in PTSD patients, too. Overall, those findings suggest that fear-related areas are involved in PTSD patients' processing of trauma-related stimuli even if the stimuli that were used in the study were task-irrelevant.

Keywords: post-traumatic stress disorder, automatic processing, hippocampus, functional magnetic resonance imaging

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj

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The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.

Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering

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Authors: Virginia Venturini, Elisabet Walker, Aylen Carrasco-Millan

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Latin America stands at the front of climate change impacts, with forecasts projecting accelerated temperature and sea level rises compared to the global average. These changes are set to trigger a cascade of effects, including coastal retreat, intensified droughts in some nations, and heightened flood risks in others. In Argentina, wildfires historically affected forests, but since 2004, wetland fires have emerged as a pressing concern. By 2021, the wetlands of the Paraná River faced a dangerous situation. In fact, during the year 2021, a high-risk scenario was naturally formed in the wetlands of the Paraná River, in Argentina. Very low water levels in the rivers, and excessive standing dead plant material (fuel), triggered most of the fires recorded in the vast wetland region of the Paraná during 2020-2021. During 2008 fire events devastated nearly 15% of the Paraná Delta, and by late 2021 new fires burned more than 300,000 ha of these same wetlands. Therefore, the goal of this work is to explore remote sensing tools to monitor environmental conditions and the severity of prescribed burns in the Paraná River wetlands. Thus, two prescribed burning experiments were carried out in the study area (31°40’ 05’’ S, 60° 34’ 40’’ W) during September 2023. The first experiment was carried out on Sept. 13th, in a plot of 0.5 ha which dominant vegetation were Echinochloa sp., and Thalia, while the second trial was done on Sept 29th in a plot of 0.7 ha, next to the first burned parcel; here the dominant vegetation species were Echinochloa sp. and Solanum glaucophyllum. Field campaigns were conducted between September 8th and November 8th to assess the severity of the prescribed burns. Flight surveys were conducted utilizing a DJI® Inspire II drone equipped with a Sentera® NDVI camera. Then, burn severity was quantified by analyzing images captured by the Sentera camera along with data from the Sentinel 2 satellite mission. This involved subtracting the NDVI images obtained before and after the burn experiments. The results from both data sources demonstrate a highly heterogeneous impact of fire within the patch. Mean severity values obtained with drone NDVI images of the first experience were about 0.16 and 0.18 with Sentinel images. For the second experiment, mean values obtained with the drone were approximately 0.17 and 0.16 with Sentinel images. Thus, most of the pixels showed low fire severity and only a few pixels presented moderated burn severity, based on the wildfire scale. The undisturbed plots maintained consistent mean NDVI values throughout the experiments. Moreover, the severity assessment of each experiment revealed that the vegetation was not completely dry, despite experiencing extreme drought conditions.

Keywords: prescribed-burn, severity, NDVI, wetlands

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Authors: A. Zaher, A. Traore, F. Thiéry, T. Talbert, B. Shaer

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In this paper, an intelligent approach is proposed to optimize the orientation of continuous solar tracking systems on cloudy days. Considering the weather case, the direct sunlight is more important than the diffuse radiation in case of clear sky. Thus, the panel is always pointed towards the sun. In case of an overcast sky, the solar beam is close to zero, and the panel is placed horizontally to receive the maximum of diffuse radiation. Under partly covered conditions, the panel must be pointed towards the source that emits the maximum of solar energy and it may be anywhere in the sky dome. Thus, the idea of our approach is to analyze the images, captured by ground-based sky camera system, in order to detect the zone in the sky dome which is considered as the optimal source of energy under cloudy conditions. The proposed approach is implemented using experimental setup developed at PROMES-CNRS laboratory in Perpignan city (France). Under overcast conditions, the results were very satisfactory, and the intelligent approach has provided efficiency gains of up to 9% relative to conventional continuous sun tracking systems.

Keywords: clouds detection, fuzzy inference systems, images processing, sun trackers

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Authors: Naomi Nathan

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Introduction Digitalization of medical education can revolutionize how medical students learn and interact with the medical curriculum across contexts. With the increasing availability of the internet and mobile connectivity in LMICs, online medical education platforms and digital learning tools are becoming more widely available, providing new opportunities for learners to access high-quality medical education and training. However, the adoption and integration of digital technologies in medical education in LMICs is a complex process influenced by various factors, including learners' perceptions and attitudes toward digital learning. In Ethiopia, the adoption of digital platforms for medical education has been slow, with traditional face-to-face teaching methods still being the norm. However, as access to technology improves and more universities adopt digital platforms, it is crucial to understand how medical students perceive this shift. Methodology This study investigated medical students' perception of the digitalization of medical education in relation to their access to the Lecturio Digital Medical Education Platform through a capacity-building project. 740 medical students from over 20 medical universities participated in the study. The students were surveyed using a questionnaire that included their attitudes toward the digitalization of medical education, their frequency of use of the digital platform, and their perceived benefits and challenges. Results The study results showed that most medical students had a positive attitude toward digitalizing medical education. The most commonly cited benefit was the convenience and flexibility of accessing course material/curriculum online. Many students also reported that they found the platform more interactive and engaging, leading to a more meaningful learning experience. The study also identified several challenges medical students faced when using the platform. The most commonly reported challenge was the need for more reliable internet access, which made it difficult for students to access content consistently. Overall, the results of this study suggest that medical students in Ethiopia have a positive perception of the digitalization of medical education. Over 97% of students continuously expressed a need for access to the Lecturio platform throughout their studies. Conclusion Significant challenges still need to be addressed to fully realize the Lecturio digital platform's benefits. Universities, relevant ministries, and various stakeholders must work together to address these challenges to ensure that medical students fully participate in and benefit from digitalized medical education - sustainably and effectively.

Keywords: digital medical education, EdTech, LMICs, e-learning

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