Search results for: acute leukaemia images

Authors: Sami Alabdulwahab

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Background: Repeated back extension exercises (RBEEs) are among the management options for symptoms associated with lumbosacral radiculopathy (LSR). RBEEs have been reported to cause changes in the distribution and intensity of radicular symptoms caused by possible compression/decompression of the compromised nerve root. Purpose: The purpose of this study was to investigate the effects of the RBEEs on the neurophysiology of the compromised nerve root and on standing mobility and pain intensity in patients with sub-acute and chronic LSR. Methods: A total of 40 patients with unilateral sub-acute/chronic lumbosacral radiculopathy voluntarily participated in the study; the patients performed 3 sets of 10 RBEEs in the prone position with 1 min of rest between the sets. The soleus H-reflex, standing mobility and pain intensity were recorded before and after the RBEEs. Results: The results of the study showed that the RBEEs significantly improved the H-reflex, standing mobility and pain intensity in patients with sub-acute LSR (p<0.01); there was not a significant improvement in the patients with chronic LSR (p<0.61). Conclusion: RBEEs in prone position is recommended for improving the neurophysiological function of the compromised nerve root and standing mobility in patients with sub-acute LSR. Implication: Sub-acute and chronic LSR responded differently to RBEEs. Sub-acute LSR appear to have flexible and movable disc structures, which could be managed with RBEEs.

Keywords: h-reflex, back extension, lumbosacral radiculopathy, pain

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Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki

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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.

Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree

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Authors: Chelly Souhir, Harizi Chahida, Hachaichi Aicha, Aissaoui Sihem, Chahed Mohamed Kouni

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Introduction: In Tunisia, few studies have attempted to describe the demand for primary care in a standardized and systematic way. The purpose of this study is to describe the main reasons for demand for care in primary health care, through a survey of the Ariana Governorate PHC and to identify their evolutionary trend compared to last 30 years, reported by studies of the same type. Materials and methods: This is a cross-sectional descriptive study which concerns the study of consultants in the first line of the governorate of Ariana and their use of care recorded during 2 days in the same week during the month of May 2016, in each of these PHC. The same data collection sheet was used in all CSBs. The coding of the information was done according to the International Classification of Primary Care (ICPC). The data was entered and analyzed by the EPI Info 7 software. Results: Our study found that the most common ICPC chapters are respiratory (42%) and digestive (13.2%). In 1996 were the respiratory (43.5%) and circulatory (7.8%). In 2000, we found also the respiratory (39,6%) and circulatory (10,9%). In 2002, respiratory (43%) and digestive (10.1%) motives were the most frequent. According to the ICPC, the pathologies in our study were acute angina (19%), acute bronchitis and bronchiolitis (8%). In 1996, it was tonsillitis ( 21.6%) and acute bronchitis (7.2%). For Ben Abdelaziz in 2000, tonsillitis (14.5%) follow by acute bronchitis (8.3%). In 2002, acute angina (15.7%), acute bronchitis and bronchiolitis (11.2%) were the most common. Conclusion: Acute angina and tonsillitis are the most common in all studies conducted in Tunisia.

Keywords: acute angina, classification of primary care, primary health care, tonsillitis, Tunisia

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Authors: Mahesh Hariharan, Rajan Balasubramaniam, Sharath Kumar Shetty, Shanthala Yadavalli, Mohammed Ahetasham, Sravya Devarapalli

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Acute abdomen is one of the most common clinical conditions requiring a radiological investigation. Ultrasound is the primary modality of choice which can diagnose some of the common causes of acute abdomen. However, sometimes the underlying cause for the pain is far more complicated than expected to mandate a high degree of suspicion to suggest further investigation with contrast-enhanced computed tomography or magnetic resonance imaging. Here, we have compiled a comprehensive series of selected cases to highlight the conditions which can be easily overlooked unless carefully sought for. This also emphasizes the importance of multimodality approach to arrive at the final diagnosis with an increased overall diagnostic accuracy which in turn improves patient management and prognosis.

Keywords: acute abdomen, contrast-enhanced computed tomography scan, magnetic resonance imaging, plain radiographs, ultrasound

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Authors: Yun-Tsuen Chen, Shih-Ting Huang, Pi-Fen Cheng, Yu-Ting Su, Joffrey Hsu, Hui-Zhu Chen

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Acute intestinal obstruction is one of the differentials of acute abdomen and requires timely alleviation of intestinal distention and abdominal pain to avoid perforation, intra-abdominal infection, and peritonitis. Investigation to identify the cause of obstruction will direct treatment planning and allow for more effective management. In this study, we present a 71-year-old female presenting with symptoms of acute intestinal obstruction for five days. After extensive history taking, physical exam, medical imaging, and pathology, the patient was diagnosed with colon cancer with lung metastasis and acute intestinal obstruction. The patient was placed on nil per os status with intravenous fluid support, intravenous antibiotics, and a decompression nasogastric tube was placed. The patient received decompression with colostomy creation surgery. After assessing the patient’s clinical condition and tumor staging, a multidisciplinary healthcare team created an individualized treatment plan, which included plans to prepare the patient for home self-care and maintain good mental health with regular monitoring in the clinic setting. This case demonstrates the importance of early diagnosis, effective treatment, and a multidisciplinary approach to the management of acute intestinal obstruction secondary to colon cancer.

Keywords: acute intestinal obstruction, colostomy surgery, metastatic colon cancer, multidisciplinary healthcare team

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Authors: Maher un Nisa, Ahsan Khawaja

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Retinal imaging with Ultra-WideField (UWF) view technology has opened up new avenues in the field of retinal pathology detection. Recent developments in retinal imaging such as Optos California Imaging Device helps in acquiring high resolution images of the retina to help the Ophthalmologists in diagnosing and analyzing eye related pathologies more accurately. This paper investigates the acquired retinal details by comparing vessel detection in standard 450 color fundus images with the state of the art 2000 UWF retinal images.

Keywords: color fundus, retinal images, ultra-widefield, vessel detection

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Authors: Edna Ariste, Richard Standy Coqmar

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Background: Acute respiratory infections are a major public health problem in the world, mainly in vulnerable populations such as newborns, children under five years of age, and the elderly. The objective of this study was to Characterize the cases of acute respiratory infections in infants and under 15 years old hospitalized at the Immaculée Conception Hospital in Cayes from January 1, 2019, to December 31, 2021. Methods: A retrospective descriptive study was conducted on the epidemiology profile of acute respiratory infections hospitalized in the pediatric ward at Immaculée Conception Hospital in Les Cayes from January 2019 to December 2021. The study population consisted of all newborns, infants, and children under 15 years of age diagnosed with respiratory infections at the pediatric service. Data were collected from the hospitalization registers and patient records of this unit. A database was created and used for data collection. Excel and Epi info 7.2 were used for data analysis. Results: A total of 588 cases were identified during the 2019-2021 year. 43.5% (256) were female, and 56.5% (332) were male. The average age was 4, 3. The most affected age group was 1-4 years. The male/female sex ratio was 1.2. The most frequent respiratory infections were respectively pneumonia 44.9%, bronchitis 16.5%, and respiratory distress 10.5%. The mortality rate recorded during this period was 4.4%. Conclusion: Acute respiratory infections are more frequent in young children. It is, therefore, necessary to practice hand hygiene. Reinforce the surveillance of severe acute respiratory infections.

Keywords: acute respiratory infections, pediatrics, cayes, haiti

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Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

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Authors: Ahd Aljarf, Saad Amin

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Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: image filtering, image reconstruction, image processing, forensic images

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Authors: Ahmed Ashit

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Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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Authors: Natalie Cutler, Lorna Moxham, Moira Stephens

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Safety is a priority in mental health services, and no more so than in the acute inpatient setting. Mental health service policies and accreditation frameworks commonly approach safety from a risk reduction or elimination perspective leading to service approaches that are arguably more focused on risk than on safety. An exploration what safety means for people who have experienced admission to an acute mental health inpatient unit is currently under way in Sydney, Australia. Using a phenomenographic research approach, this study is seeking to understand the meaning of safety from the perspective of people who use, rather than those who deliver mental health services. Preliminary findings suggest that the meanings of safety for users of mental health services vary from the meanings inherent in the policies and frameworks that inform how mental health services and mental health practice are delivered. This variance has implications for the physical and environmental design of acute mental health inpatient facilities, the policies and practices, and the education and training of mental health staff in particular nurses, who comprise the majority of the mental health workforce. These variances will be presented, along with their implications for the way quality and safety in mental health services are evaluated.

Keywords: acute inpatient, mental health, nursing, phenomenography, recovery, safety

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Authors: Sofia Matoug, Amr Abdel-Dayem

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This paper presents a comprehensive survey of recent research studies to segment and classify brain MR (magnetic resonance) images in order to detect significant changes to brain ventricles. The paper also presents a general framework for detecting regions that atrophy, which can help neurologists in detecting and staging Alzheimer. Furthermore, a prototype was implemented to segment brain MR images in order to extract the region of interest (ROI) and then, a classifier was employed to differentiate between normal and abnormal brain tissues. Experimental results show that the proposed scheme can provide a reliable second opinion that neurologists can benefit from.

Keywords: Alzheimer, brain images, classification techniques, Magnetic Resonance Images MRI

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Authors: Muhammad Mukhtar

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The aim of this study is to evaluate the antioxidant activity and acute toxicity of the extracts of Ficus iteophylla by reactions with 1, 1-diphenyl-2-picryhydrazyl radical (DPPH) and method developed by Lork 1983, respectively. Stem bark of Ficus iteophylla was collected, air dried, pulverized to fine powdered and sequentially extracted using acetone, methanol and water in order of increasing polarity. The result shows strong radical scavenging activity against DPPH for all the extracts when compared with ascorbic acid. The LD50 of 316 mg/kg was calculated for all the three extras, and the values were found to be within the practically toxic range, and therefore, care should be taken when using the plants in traditional medicine.

Keywords: antioxidant, acute toxicity, Ficus iteophylla

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Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

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Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: medical resonance (MR) images, difference mean opinion score (DMOS), full reference image quality assessment (FR-IQA)

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Authors: Astrid Tannert, Anuradha Ramoji, Christina Ebert, Frederike Gladigau, Lorena Tuchscherr, Jürgen Popp, Ute Neugebauer

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Staphylococcus aureus is a facultative intracellular pathogen, which by entering host cells may evade immunologic host response as well as antimicrobial treatment. In that way, S. aureus can cause persistent intracellular infections which are difficult to treat. Depending on the strain, S. aureus may persist at different intracellular locations like the phagolysosome. The first barrier invading pathogens from the blood stream that they have to cross are the endothelial cells lining the inner surface of blood and lymphatic vessels. Upon proceeding from an acute to a chronic infection, intracellular pathogens undergo certain biochemical and structural changes including a deceleration of metabolic processes to adopt for long-term intracellular survival and the development of a special phenotype designated as small colony variant. In this study, the endothelial cell line Ea.hy 926 was used as a model for acute and chronic S. aureus infection. To this end, Ea.hy 926 cells were cultured on QIAscout™ Microraft Arrays, a special graded cell culture substrate that contains around 12,000 microrafts of 200 µm edge length. After attachment to the substrate, the endothelial cells were infected with GFP-expressing S. aureus for 3 weeks. The acute infection and the development of persistent bacteria was followed by confocal laser scanning microscopy, scanning the whole Microraft Array for the presence and for detailed determination of the intracellular location of fluorescent intracellular bacteria every second day. After three weeks of infection representative microrafts containing infected cells, cells with protruded infections and cells that did never show any infection were isolated and fixed for Raman micro-spectroscopic investigation. For comparison, also microrafts with acute infection were isolated. The acquired Raman spectra are correlated with the fluorescence microscopic images to give hints about a) the molecular alterations in endothelial cells during acute and chronic infection compared to non-infected cells, and b) metabolic and structural changes within the pathogen when entering a mode of persistence within host cells. We thank Dr. Ruth Kläver from QIAGEN GmbH for her support regarding QIAscout technology. Financial support by the BMBF via the CSCC (FKZ 01EO1502) and from the DFG via the Jena Biophotonic and Imaging Laboratory (JBIL, FKZ PO 633/29-1, BA 1601/10-1) is highly acknowledged.

Keywords: correlative image analysis, intracellular infection, pathogen-host adaption, Raman micro-spectroscopy

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Authors: Haoqi Gao, Koichi Ogawara

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Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method.

Keywords: retinal vascular segmentations, generative ad-versarial network, cyclegan, fundus images

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Authors: Barun K. De

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Acquired immunodeficiency syndrome (AIDS) is caused by two types of human immunodeficiency viruses, collectively designated HIV. HIV infection is spreading globally particularly in developing countries. Before an individual is diagnosed with HIV, the disease goes through different phases. First there is an acute early phase that is followed by an established or chronic phase. Subsequently, there is a latency period after which the individual becomes immunodeficient. It is in the acute phase that an individual is highly infectious due to a high viral load. Presently, HIV diagnosis involves use of tests that do not detect the acute phase infection during which both the viral RNA and p24 antigen are expressed. Instead, these less sensitive tests detect antibodies to viral antigens which are typically sero-converted later in the disease process following acute infection. These antibodies are detected in both asymptomatic HIV-infected individuals as well as AIDS patients. Studies indicate that early diagnosis and treatment of HIV infection can reduce medical costs, improve survival, and reduce spreading of infection to new uninfected partners. Newer 4th generation combination antigen/antibody tests are highly sensitive and specific for detection of acute and established HIV infection (HIV1 and HIV2) enabling immediate linkage to care. The CDC (Center of Disease Control, USA) recently recommended an algorithm involving three different tests to screen and diagnose acute and established infections of HIV-1 and HIV-2 in a general population. Initially a 4th generation combo test detects a viral antigen p24 and specific antibodies against HIV -1 and HIV-2 envelope proteins. If the test is positive it is followed by a second test known as a differentiation assay which detects antibodies against specific HIV-1 and HIV-2 envelope proteins confirming established infection of HIV-1 or HIV-2. However if it is negative then another test is performed that measures viral load confirming an acute HIV-1 infection. Screening results of a Phoenix area population detected 0.3% new HIV infections among which 32.4% were acute cases. Studies in the U.S. indicate that this algorithm effectively reduces HIV infection through immediate treatment and education following diagnosis.

Keywords: new algorithm, HIV, diagnosis, infection

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Authors: Roni Rachel Mendelson, Caileigh Pudela

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Bacillus cereus is a toxin-producing, facultatively anaerobic gram-positive bacterium that is widely distributed environmentally. It can quickly multiply at room temperature with an abundantly present preformed toxin. When ingested, this toxin can cause gastrointestinal illness, which is the commonly known manifestation of the disease. Bacillus cereus sepsis is a disease that is mostly concerning in the population of the immunocompromised patients. One of them is acute lymphoblastic leukemia’s patients during induction. Pediatric acute lymphoblastic leukemia is a common pediatric hematologic malignancy. It is characterized by the rapid proliferation of poorly differentiated lymphoid progenitor cells inside the bone marrow. We present here a 21-month-old boy undergoing induction chemotherapy for acute lymphoblastic leukemia who developed bacillus sepsis bacteremia and, as a result, multi organ failure leading to seizures and multiple strokes. Our case report highlights the extensive overall and neurological damage that can be caused because of bacillus cereus bacteremia, which can lead to higher mortality rate and decreased in survivorship in a highly curable disease. It is very subtle and difficult to recognize and appears to be deteriorating extremely fast. There should be a low threshold for work up and empiric coverage for neutropenic patients during acute lymphoblastic leukemia induction therapy.

Keywords: acute lymphoblastic leukemia, bacillus cereus, immunocompromised, sepsis

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Authors: Sujatha Shanmugasundaram

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Background: It has been since one year that COVID-19 has emerged into the world. Since then, healthcare professionals facing a great challenge in to fight against this deadly virus. According to World Health Organization (WHO) 2021, it is estimated that more than 131 million confirmed cases and 2million deaths around the world due to this pandemic. Nurses are the frontline workers who play a major role in safeguarding the lives of the people in acute care settings. Evidence suggests that there are numbers of research have been carried out on nurses' and healthcare provider’s experiences during the pandemic. But, unfortunately, there are no or little evidence available on Muslim nurse’s perspective. Hence, this research will investigate the experiences of Muslim nurses working in an acute care setting during the pandemic. Purpose: The purpose of the study is to explore the experiences of Muslim nurses working in an acute setting during the COVID-19 pandemic. Research Methods: A qualitative research approach will be utilized for the study. Semi-structured interview schedule will be used to collect the data. Face to face interviews will be conducted. All interviews will be conducted in Arabic, and it will be audio recorded. Verbatim will be noted. Muslim nurses working in an acute setting will be included in the study. Convenient sampling technique will be used to recruit the participants. Ethical approval will be obtained from the study sites. Strauss and Corbin's thematic analysis will be used to analyze the data. Conclusion: Considering that nurses are the frontline workers, they have a significant role in dealing with this COVID-19. It is a great challenge for the nurses working in an acute care setting. Thus, this study will bring out significant findings that will impact the nursing practice.

Keywords: acute care, COVID-19, experiences, muslim nurses

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Authors: H. Ali, A. Whitehead

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Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.

Keywords: cultural heritage, image registration, image subset selection, registered image similarity, temporal panorama, timescapes

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Satoshi Furukawa, Satomu Morita, Katsuji Nishi, Masahito Hitosugi

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Coronary artery dissection leading to acute myocardial infarction after blunt chest trauma is extremely rare. A 67-year-old woman suffered blunt chest trauma following a traffic accident. The electrocardiogram revealed acute posterior ST-segment elevation and myocardial infarction and coronary angiography demonstrated acute right coronary artery dissection. Following the death of the victim an autopsy was performed after cardiopulmonary support had been carried out. In this case report, we describe the case of a woman with blunt chest trauma, who developed an acute myocardial infarction secondary to right coronary artery dissection. Although there was additional the blunt chest trauma due to chest compression, we confirmed the injury at autopsy and by histological findings.

Keywords: blunt chest trauma, right coronary artery dissection, coronary angiography, autopsy, histological examination

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Authors: Kristel Dame Bañez Sumagaysay, Marie Victoria Cruz-javier

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The current subject is a case of a 21 year-old woman at 29 1/7 weeks of gestation with Pre-B cell Acute Lymphoblastic Leukemia who was admitted to the coronary care unit (CCU) of the St. Luke’s Medical Center-Global City for Severe Acute Respiratory Distress Syndrome (ARDS) secondary to hospital-acquired pneumonia secondary to pneumocystis jiroveci; central line-associated bloodstream infection (E. aerogenes). She presented with chronic hypoxemia caused by Pulmonary edema, probably secondary to heart failure secondary to cardiomyopathy chemotherapy-induced. Due to worsening feto-maternal status, extracorporeal membrane oxygenation (ECMO) for respiratory support was instituted, and an elective cesarean section was done due to multiple maternal factors and deteriorating health status under total intravenous anesthesia assisted by veno-venous extracorporeal membrane oxygenation. She delivered a live preterm newborn male, APGAR Score: 1, 0, 0, birth weight 985 grams, birth length: 40.5cm, small for gestational age.

Keywords: extracorporeal membrane oxygenation, pre-b cell acute lymphoblastic leukemia, severe acute respiratory distress syndrome, ethical dilemmas

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Authors: Aissa Belmeguenai, Oulaya Berrak, Khaled Mansouri

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In this work, efficiency implementation and security evaluation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation.

Keywords: Achterbahn-128, keystream generator, stream cipher, image encryption, security analysis

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Authors: Kohei Inoue, Kenji Hara, Kiichi Urahama

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We describe a relationship between integral images and differential images. First, we derive a simple difference filter from conventional integral image. In the derivation, we show that an integral image and the corresponding differential image are related to each other by simultaneous linear equations, where the numbers of unknowns and equations are the same, and therefore, we can execute the integration and differentiation by solving the simultaneous equations. We applied the relationship to an image fusion problem, and experimentally verified the effectiveness of the proposed method.

Keywords: integral images, differential images, differential filters, image fusion

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Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

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Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

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Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

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Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

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Authors: Sajidullah Khan, Najeeb Ullah, Wang Yin Chai, Chai Soo See

Abstract:

In this paper, we propose an approach to remove impulse and Poisson noise from X-ray images. Many filters have been used for impulse noise removal from color and gray scale images with their own strengths and weaknesses but X-ray images contain Poisson noise and unfortunately there is no intelligent filter which can detect impulse and Poisson noise from X-ray images. Our proposed filter uses the upgraded layer discrimination approach to detect both Impulse and Poisson noise corrupted pixels in X-ray images and then restores only those detected pixels with a simple efficient and reliable one line equation. Our Proposed algorithms are very effective and much more efficient than all existing filters used only for Impulse noise removal. The proposed method uses a new powerful and efficient noise detection method to determine whether the pixel under observation is corrupted or noise free. Results from computer simulations are used to demonstrate pleasing performance of our proposed method.

Keywords: X-ray image de-noising, impulse noise, poisson noise, PRWF

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Authors: Aissa Belmeguenai, Khaled Mansouri

Abstract:

In this work, an efficient implementation of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written by MATLAB.7.5. At first two different original images are used for validate the proposed design. Then our developed program was used to transform the original images data into image digits file. Finally, we used our implemented program to encrypt and decrypt images data. Several tests are done for proving the design performance including visual tests and security analysis; we discuss the security analysis of the proposed image encryption scheme including some important ones like key sensitivity analysis, key space analysis, and statistical attacks.

Keywords: Achterbahn-128, stream cipher, image encryption, security analysis

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Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith

Abstract:

Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.

Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution

Procedia PDF Downloads 57