Search results for: B-mode Ultrasound Image

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Dalila Chaid, Bennameur Fedilli, Mohammed Amine Bellelou

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The study focuses on the experience of lower-limb amputees, who face both physical and psychological challenges due to their disability. Chronic neuropathic pain and various types of limb pain are common in these patients. They often require orthopaedic interventions for issues such as dressings, infection, ulceration, and bone-related problems. Research Aim: The aim of this study is to determine the most suitable anaesthetic technique for lower-limb amputees, which can provide them with the greatest comfort and prolonged analgesia. The study also aims to demonstrate the effectiveness and cost-effectiveness of ultrasound-guided local regional anaesthesia (LRA) in this patient population. Methodology: The study is an observational analytical study conducted over a period of eight years, from 2010 to 2018. It includes a total of 955 cases of revisions performed on lower limb stumps. The parameters analyzed in this study include the effectiveness of the block and the use of sedation, the duration of the block, the post-operative visual analog scale (VAS) scores, and patient comfort. Findings: The study findings highlight the benefits of ultrasound-guided LRA in providing comfort by optimizing post-operative analgesia, which can contribute to psychological and bodily repair in lower-limb amputees. Additionally, the study emphasizes the use of alpha2 agonist adjuvants with sedative and analgesic properties, long-acting local anaesthetics, and larger volumes for better outcomes. Theoretical Importance: This study contributes to the existing knowledge by emphasizing the importance of choosing an appropriate anaesthetic technique for lower-limb amputees. It highlights the potential of ultrasound-guided LRA and the use of specific adjuvants and local anaesthetics in improving post-operative analgesia and overall patient outcomes. Data Collection and Analysis Procedures: Data for this study were collected through the analysis of medical records and relevant documentation related to the 955 cases included in the study. The effectiveness of the anaesthetic technique, duration of the block, post-operative pain scores, and patient comfort were analyzed using statistical methods. Question Addressed: The study addresses the question of which anaesthetic technique would be most suitable for lower-limb amputees to provide them with optimal comfort and prolonged analgesia. Conclusion: The study concludes that ultrasound-guided LRA, along with the use of alpha2 agonist adjuvants, long-acting local anaesthetics, and larger volumes, can be an effective approach in providing comfort and improving post-operative analgesia for lower-limb amputees. This technique can potentially contribute to the psychological and bodily repair of these patients. The findings of this study have implications for clinical practice in the management of lower-limb amputees, highlighting the importance of personalized anaesthetic approaches for better outcomes.

Keywords: neuropathic pain, ultrasound-guided peripheral nerve block, DN4 quiz, EMG

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Bouafia-Chergui Souâd, Chabani Malika, Bensmaili Aicha

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Water treatment and especially, medicament pollutants are nowadays important problems. Degradation of oxytetracycline was carried out using combined process of low-frequency ultrasound (US), ultraviolet irradiation and a catalyst. The effectiveness of the coupled processes has been evaluated by studying the effects of various operating parameters including initial OTC concentration, solution pH and catalyst mass. For the photolysis process, the monochromatic ultraviolet light wavelength utilized was 365 nm. The sonolysis experiments were performed with ultrasound at a frequency of 40 kHz. The heterogeneous photocatalysis was studied in the presence of TiO2. The processes were employed individually, and simultaneously to examine the details of the processes and to investigate the contribution of each process. Low UV intensity (12W), low pH and high mass of TiO2 conditions enhanced the sono-photocatalytic degradation of OTC. The results showed that the individual contribution sonochemical and photochemical reactions are very low, however, their coupling increases the degradation rate of 8 times compared to photolysis and 2 times compared to sonolysis. There is a synergistic effect between the two modes of radiation, UV and U.S. leading to 82.04% degradation yield. An application of these combined processes on the treatment of a real pharmaceutical wastewater was examined.

Keywords: sonolysis, photocatalysis, combined process, antibiotic

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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Authors: Arjun Prakash, Vinutha H., Karthik N.

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BACKGROUND: Carpal tunnel syndrome (CTS) is a common entrapment neuropathy with an estimated prevalence of 0.6 - 5.8% in the general adult population. It is caused by compression of the Median Nerve (MN) at the wrist as it passes through a narrow osteofibrous canal. Presently, the diagnosis is established by the clinical symptoms and physical examination and Nerve conduction study (NCS) is used to assess its severity. However, it is considered to be painful, time consuming and expensive, with a false-negative rate between 16 - 34%. Ultrasonography (USG) is now increasingly used as a diagnostic tool in CTS due to its non-invasive nature, increased accessibility and relatively low cost. Elastography is a newer modality in USG which helps to assess stiffness of tissues. However, there is limited available literature about its applications in peripheral nerves. OBJECTIVES: Our objectives were to measure the Cross-Sectional Area (CSA) and elasticity of MN at the carpal tunnel using Grey scale Ultrasonography (USG), Strain Elastography (SE) and Shear Wave Elastography (SWE). We also made an attempt to independently evaluate the role of Gray scale USG, SE and SWE in grading the severity of CTS, keeping NCS as the gold standard. MATERIALS AND METHODS: After approval from the Institutional Ethics Review Board, we conducted a comparative cross sectional study for a period of 18 months. The participants were divided into two groups. Group A consisted of 54 patients with clinically diagnosed CTS who underwent NCS, and Group B consisted of 50 controls without any clinical symptoms of CTS. All Ultrasound examinations were performed on SAMSUNG RS 80 EVO Ultrasound machine with 2 - 9 Mega Hertz linear probe. In both groups, CSA of the MN was measured on Grey scale USG, and its elasticity was measured at the carpal tunnel (in terms of Strain ratio and Shear Modulus). The variables were compared between both groups by using ‘Independent t test’, and subgroup analyses were performed using one-way analysis of variance. Receiver operating characteristic curves were used to evaluate the diagnostic performance of each variable. RESULTS: The mean CSA of the MN was 13.60 + 3.201 mm2 and 9.17 + 1.665 mm2 in Group A and Group B, respectively (p < 0.001). The mean SWE was 30.65 + 12.996 kPa and 17.33 + 2.919 kPa in Group A and Group B, respectively (p < 0.001), and the mean Strain ratio was 7.545 + 2.017 and 5.802 + 1.153 in Group A and Group B respectively (p < 0.001). CONCLUSION: The combined use of Gray scale USG, SE and SWE is extremely useful in grading the severity of CTS and can be used as a painless and cost-effective alternative to NCS. Early diagnosis and grading of CTS and effective treatment is essential to avoid permanent nerve damage and functional disability.

Keywords: carpal tunnel, ultrasound, elastography, nerve conduction study

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Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

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This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

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Authors: Asmaa Hamdy, Israa Nassar, Tarek Aly

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Introduction: Femoral fractures are the most common presentation in the Emergency Department (ED), and they can present as isolated injuries or as part of a polytrauma situation. To provide optimum pain management care to these patients, practitioners must be well prepared and current with utilizing modern evidence-based knowledge and practices. Management of pain associated with fracture femur in the emergency department has a critical role in the satisfaction of patients and preventing further complications. This study aimed to evaluate the analgesic efficacy of ultrasound-guided femoral nerve block compared with intravenous fentanyl in fractures of the femur in patients presented to the Emergency Department. Patients and Methods: Fifty patients with femur fractures were divided into two groups: Group A: In this group (twenty-five patients) were given intravenous fentanyl 2 micro-grams/kg and re-assessed for pain by Visual Analogue Score (VAS). Group B: In this group (twenty-five patients) underwent ultrasonography-guided femoral nerve block and were re-assessed for pain by VAS. Results: VAS score on the movement of the fractured limb between group A and group B at a 10-minute post-intervention period shows P= 0.043, and hence the difference is significant. VAS score on the movement of the fractured limb between group A and group B during a 10-minute post-intervention period showed a significant difference. Seventeen patients in group A had major PID with a percentage of 63% VS 10 patients in group B with a percentage of 37%. conclusion: both femoral nerve block and intravenous fentanyl are effective in relieving pain in patients with femur fractures. But femoral nerve block provides better and more intense analgesia and major pain intensity difference in less time. Moreover, the use of FNB had fewer side effects and more Hemodynamics stability compared to opioids.

Keywords: femur fracture, nerve block, fentanyl, ultrasound guided

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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Authors: Maryam Mohammad Hadi, Heather Nesbitt, Hamzah Masood, Hashim Ahmed, Mark Emberton, John Callan, Alexander MacRobert, Anthony McHale, Nikolitsa Nomikou

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Sonodynamic therapy (SDT) utilises ultrasound in combination with sensitizers, such as porphyrins, for the production of cytotoxic reactive oxygen species (ROS) and the confined ablation of tumours. Ultrasound can be applied locally, and the acoustic waves, at frequencies between 0.5-2 MHz, are transmitted efficiently through tissue. SDT does not require highly toxic agents, and the cytotoxic effect only occurs upon ultrasound exposure at the site of the lesion. Therefore, this approach is not associated with adverse side effects. Further highlighting the benefits of SDT, no cancer cell population has shown resistance to therapy-triggered ROS production or their cytotoxic effects. This is particularly important, given the as yet unresolved issues of radiation and chemo-resistance, to the authors’ best knowledge. Another potential future benefit of this approach – considering its non-thermal mechanism of action – is its possible role as an adjuvant to immunotherapy. Substantial pre-clinical studies have demonstrated the efficacy and targeting capability of this therapeutic approach. However, SDT has yet to be fully characterised and appropriately exploited for the treatment of cancer. In this study, a formulation based on multistimulus-responsive sensitizer-containing nanoparticles that can accumulate in advanced prostate tumours and increase the therapeutic efficacy of SDT has been developed. The formulation is based on a polyglutamate-tyrosine (PGATyr) co-polymer carrying hematoporphyrin. The efficacy of SDT in this study was demonstrated using prostate cancer as the translational exemplar. The formulation was designed to respond to the microenvironment of advanced prostate tumours, such as the overexpression of the proteolytic enzymes, cathepsin-B and prostate-specific membrane antigen (PSMA), that can degrade the nanoparticles, reduce their size, improving both diffusions throughout the tumour mass and cellular uptake. The therapeutic modality was initially tested in vitro using LNCaP and PC3 cells as target cell lines. The SDT efficacy was also examined in vivo, using male SCID mice bearing LNCaP subcutaneous tumours. We have demonstrated that the PGATyr co-polymer is digested by cathepsin B and that digestion of the formulation by cathepsin-B, at tumour-mimicking conditions (acidic pH), leads to decreased nanoparticle size and subsequent increased cellular uptake. Sonodynamic treatment, at both normoxic and hypoxic conditions, demonstrated ultrasound-induced cytotoxic effects only for the nanoparticle-treated prostate cancer cells, while the toxicity of the formulation in the absence of ultrasound was minimal. Our in vivo studies in immunodeficient mice, using the hematoporphyrin-containing PGATyr nanoparticles for SDT, showed a 50% decrease in LNCaP tumour volumes within 24h, following IV administration of a single dose. No adverse effects were recorded, and body weight was stable. The results described in this study clearly demonstrate the promise of SDT to revolutionize cancer treatment. It emphasizes the potential of this therapeutic modality as a fist line treatment or in combination treatment for the elimination or downstaging of difficult to treat cancers, such as prostate, pancreatic, and advanced colorectal cancer.

Keywords: sonodynamic therapy, nanoparticles, tumour ablation, ultrasound

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Authors: Olivier Mulisya, Guelord Barasima, Henry Mark Lugobe, Philémon Matumo, Bienfait Mumbere Vahwere, Hilaire Mutuka, Zawadi Léocadie, Wesley Lumika

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Abdominal pregnancy is defined as pregnancy anywhere within the peritoneal cavity, exclusive of tubal, ovarian, or broad ligament locations. It is a rare form of ectopic pregnancy with high morbidity and mortality for both the mother and the fetus. Diagnosis can be frequently missed in most poor-resource settings because of poor antenatal coverage, low socioeconomic status in most of the patients as well as lack of adequate medical resources. Clinical diagnosis can be very difficult and an ultrasound scan is very helpful during the early stages of gestation but can also be disappointing in the later stages. We report a case of a 25-year-old woman with severe abdominal pain not amended with any medication. A clinical picture of shock lead to an emergency laparotomy which confirmed the diagnosis of abdominal pregnancy. The ministry of health in developing countries should make an effort to make routine early ultrasounds accessible to pregnant women, and obstetricians should keep in mind the possibility of ectopic pregnancy, irrespective of the gestational age.

Keywords: abdominal pregnancy, live new bron, ultrasound imaging, abdominal pain

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Authors: Zihan Yu, Kohei Inoue, Kiichi Urahama

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

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

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Authors: Kevin Wongleedee

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The purposes of this research were to study the image of a flight attendant career from the perspective of high school students in Bangkok and to study the level of interest to pursue a flight attendant career. A probability random sampling of 400 students was utilized. Half the sample group came from private high schools and the other half came from public high schools. A questionnaire was used to collect the data and small in-depth interviews were also used to get their opinions about the image and their level of interest in the flight attendant career. The findings revealed that the majority of respondents had a medium level of interest in the flight attendant career. High school students who majored in Math-English were more interested in a flight attendant career than high school students who majored in Science-Math with a 0.05 level of significance. The image of flight attendant career was rated as a good career with a chance to travel to many countries. The image of flight attendance career can be ranked as follows: a career with a chance to travel, a career with ability to speak English, a career that requires punctuality, a career with a good service mind, and a career with an understanding of details. The findings from the in-depth interviews revealed that the major obstacles that prevented high school students from choosing a flight attendant as a career were their ability to speak English, their body proportions, and lack of information.

Keywords: flight attendant, high school students, image, media engineering

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Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

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Authors: Seda Sahin, Emin Akata

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Obturator foramen is a specific structure in pelvic bone images and recognition of it is a new concept in medical image processing. Moreover, segmentation of bone structures such as obturator foramen plays an essential role for clinical research in orthopedics. In this paper, we present a novel method to analyze the similarity between the substructures of the imaged region and a hand drawn template, on hip radiographs to detect obturator foramen accurately with integrated usage of Marker-controlled Watershed segmentation and Zernike moment feature descriptor. Marker-controlled Watershed segmentation is applied to seperate obturator foramen from the background effectively. Zernike moment feature descriptor is used to provide matching between binary template image and the segmented binary image for obturator foramens for final extraction. The proposed method is tested on randomly selected 100 hip radiographs. The experimental results represent that our method is able to segment obturator foramens with % 96 accuracy.

Keywords: medical image analysis, segmentation of bone structures on hip radiographs, marker-controlled watershed segmentation, zernike moment feature descriptor

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Authors: Boris M. Popović, Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović

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Green solvents are environmentally friendly and greatly improve the sustainability of chemical processes. There is a growing interest in the green extraction of polyphenols from fruits. In this study, we consider three Natural Deep Eutectic Solvents (NADES) systems based on choline chloride as a hydrogen bond acceptor and malic acid, urea, and fructose as hydrogen bond donors. NADES systems were prepared by heating and stirring, ultrasound, and microwave (MW) methods. Sour cherry pomace was used as a natural source of polyphenols. Polyphenol extraction from cherry pomace was performed by ultrasound-assisted extraction and microwave-assisted extraction and compared with conventional heat and stirring method extraction. It was found that MW-assisted preparation of NADES was the fastest, requiring less than 30 s. Also, MW extraction of polyphenols was the most rapid, with less than 5 min necessary for the extract preparation. All three NADES systems were highly efficient for anthocyanin extraction, but the most efficient was the system with malic acid as a hydrogen bond donor (yield of anthocyanin content was enhanced by 62.33% after MW extraction with NADES compared with the conventional solvent).

Keywords: anthocyanins, green extraction, NADES, polyphenols

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

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

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

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Authors: Hamid R. Chabok, Demetrios N. Christodoulides, Mercedeh Khajavikhan

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In recent years, acousto-optic (AO) lenses with tunable foci have emerged as a powerful tool for optical beam shaping, imaging, and particle manipulation. In most current AO lenses, the incident light that propagates orthogonally to a standing ultrasonic wave converts to a Bessel-like beam pattern due to the Raman-Nath effect, thus forming annular fringes that result in compromised focus response. Here, we report a new class of AO dynamic lensing based on generating a 3D-variable refractive index profile via a z-axis-scan ultrasound transducer. By utilizing the co- /counter propagation of light and acoustic waves that interact over a longer distance, the laser beam can be strongly focused in a fully controllable manner. Using this approach, we demonstrate AO lenses with instantaneous extended depth of field (DoF) and laterally localized dynamic focusing. This new light-sound interaction scheme may pave the way towards applications that require remote focusing, 3D micromanipulation, and deep tissue therapy/imaging.

Keywords: acousto-optic, optical beam shaping, dynamic lensing, ultrasound

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

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Authors: Kuo-Cheng Liu

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In the perceptual image coding, the objective is to shape the coding distortion such that the amplitude of distortion does not exceed the error visibility threshold, or to remove perceptually redundant signals from the image. While most researches focus on color image coding, the perceptual-based quantizer developed for luminance signals are always directly applied to chrominance signals such that the color image compression methods are inefficient. In this paper, the internal generative mechanism is integrated into the design of a color image compression method. The internal generative mechanism working model based on the structure-based spatial masking is used to assess the subjective distortion visibility thresholds that are visually consistent to human eyes better. The estimation method of structure-based distortion visibility thresholds for color components is further presented in a locally adaptive way to design quantization process in the wavelet color image compression scheme. Since the lowest subband coefficient matrix of images in the wavelet domain preserves the local property of images in the spatial domain, the error visibility threshold inherent in each coefficient of the lowest subband for each color component is estimated by using the proposed spatial error visibility threshold assessment. The threshold inherent in each coefficient of other subbands for each color component is then estimated in a local adaptive fashion based on the distortion energy allocation. By considering that the error visibility thresholds are estimated using predicting and reconstructed signals of the color image, the coding scheme incorporated with locally adaptive perceptual color quantizer does not require side information. Experimental results show that the entropies of three color components obtained by using proposed IGM-based color image compression scheme are lower than that obtained by using the existing color image compression method at perceptually lossless visual quality.

Keywords: internal generative mechanism, structure-based spatial masking, visibility threshold, wavelet domain

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Authors: Aika Umemuro, Mitsuru Sato, Mizuki Narita, Saya Hori, Saya Sakurai, Tomomi Nakayama, Ayano Nakazawa, Toshihiro Ogura

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Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.

Keywords: EEG scanner, eye-detector, mammography, observers

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Authors: Sathyaseelan Subramaniam, Jacqueline Bober, Jennifer Chao, Shahriar Zehtabchi

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Background: Emergency physicians frequently evaluate skin and soft tissue infections in order to differentiate abscess from cellulitis. This helps determine which patients will benefit from incision and drainage. Our objective was to determine the operating characteristics of point-of-care ultrasound (POCUS) compared to clinical examination in identifying abscesses in emergency department (ED) patients with features of skin and soft tissue infections. Methods: We performed a comprehensive search in the following databases: Medline, Web of Science, EMBASE, CINAHL and Cochrane Library. Trials were included if they compared the operating characteristics of POCUS with clinical examination in identifying skin and soft tissue abscesses. Trials that included patients with oropharyngeal abscesses or that requiring abscess drainage in the operating room were excluded. The presence of an abscess was determined by pus drainage. No pus seen on incision or resolution of symptoms without pus drainage at follow up, determined the absence of an abscess. Quality of included trials was assessed using GRADE criteria. Operating characteristics of POCUS are reported as sensitivity, specificity, positive likelihood (LR+) and negative likelihood (LR-) ratios and the respective 95% confidence intervals (CI). Summary measures were calculated by generating a hierarchical summary receiver operating characteristic model (HSROC). Results: Out of 3203 references identified, 5 observational studies with 615 patients in aggregate were included (2 adults and 3 pediatrics). We rated the quality of 3 trials as low and 2 as very low. The operating characteristics of POCUS and clinical examination in identifying soft tissue abscesses are presented in the table. The HSROC for POCUS revealed a sensitivity of 96% (95% CI = 89-98%), specificity of 79% (95% CI = 71-86), LR+ of 4.6 (95% CI = 3.2-6.8), and LR- of 0.06 (95% CI = 0.02-0.2). Conclusion: Existing evidence indicates that POCUS is useful in identifying abscesses in ED patients with skin or soft tissue infections.

Keywords: abscess, point-of-care ultrasound, pocus, skin and soft tissue infection

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Authors: M. Kumpugdee-Vollrath, J.-P. Krause, S. Bürk

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Most of the drugs used for pharmaceutical purposes are poorly water-soluble drugs. About 40% of all newly discovered drugs are lipophilic and the numbers of lipophilic drugs seem to increase more and more. Drug delivery systems such as nanoparticles, micelles or liposomes are applied to improve their solubility and thus their bioavailability. Besides various techniques of solubilization, oil-in-water emulsions are often used to incorporate lipophilic drugs into the oil phase. To stabilize emulsions surface active substances (surfactants) are generally used. An alternative method to avoid the application of surfactants was of great interest. One possibility is to develop O/W-emulsion without any addition of surface active agents or the so called “surfactant-free emulsion or SFE”. The aim of this study was to develop and characterize SFE as a drug carrier by varying the production conditions. Lidocaine base was used as a model drug. The injection method was developed. Effects of ultrasound as well as of temperature on the properties of the emulsion were studied. Particle sizes and release were determined. The long-term stability up to 30 days was performed. The results showed that the surfactant-free O/W emulsions with pharmaceutical oil as drug carrier can be produced.

Keywords: emulsion, lidocaine, Miglyol, size, surfactant, light scattering, release, injection, ultrasound, stability

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Authors: Yoganathan Karthik, Guhanathan Poravi

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Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

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Authors: Shayan Rezvanigilkolaei, Shayesteh Vefaghnematollahi

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Electrical impedance tomography is a non-invasive medical imaging technique suitable for medical applications. This paper describes an electrical impedance tomography device with the ability to navigate a robotic arm to manipulate a target object. The design of the device includes various hardware and software sections to perform medical imaging and control the robotic arm. In its hardware section an image is formed by 16 electrodes which are located around a container. This image is used to navigate a 3DOF robotic arm to reach the exact location of the target object. The data set to form the impedance imaging is obtained by having repeated current injections and voltage measurements between all electrode pairs. After performing the necessary calculations to obtain the impedance, information is transmitted to the computer. This data is fed and then executed in MATLAB which is interfaced with EIDORS (Electrical Impedance Tomography Reconstruction Software) to reconstruct the image based on the acquired data. In the next step, the coordinates of the center of the target object are calculated by image processing toolbox of MATLAB (IPT). Finally, these coordinates are used to calculate the angles of each joint of the robotic arm. The robotic arm moves to the desired tissue with the user command.

Keywords: electrical impedance tomography, EIT, surgeon robot, image processing of electrical impedance tomography

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Authors: Toshanlal Meenpal, Ankita Meenpal

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A very important technique in reversible data hiding field is Difference expansion. Secret message as well as the cover image may be completely recovered without any distortion after data extraction process due to reversibility feature. In general, in any difference expansion scheme embedding is performed by integer transform in the difference image acquired by grouping two neighboring pixel values. This paper proposes an improved reversible difference expansion embedding scheme. We mainly consider edge direction for embedding by modifying the difference of two neighboring pixels values. In general, the larger difference tends to bring a degraded stego image quality than the smaller difference. Image quality in the range of 0.5 to 3.7 dB in average is achieved by the proposed scheme, which is shown through the experimental results. However payload wise it achieves almost similar capacity in comparisons with previous method.

Keywords: information hiding, wedge direction, difference expansion, integer transform

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Authors: Samrah Saeed

Abstract:

Introduction: This study considers a measure of positive body image and the associations between body appreciation, beauty ideals internalization, dietary habits, and physical activity in young adults. Positive body image is assessed by Body Appreciation Scale 2. It is used to assess a person's acceptance of the body, the degree of positivity, and respect for the body.Regular physical activity and healthy eating arebasically important for the body, and they play an important role in creating a positive image of the body. Objectives: To identify the associations between body appreciation and beauty ideals internalization. To compare body appreciation and body ideals internalization among students of different physical activity. To explore the associations between dietary habits (unhealthy, healthy), body appreciation and body ideals internalization. Research methods and organization: Study participants were young adult students, aged 18-35, both male and female.The research questionnaire consisted of four areas: body appreciation, beauty ideals internalization, dietary habits, and physical activity.The questionnaire was created in Google Forms online survey platform.The questionnaire was filled out anonymously Result and Discussion: Physical dissatisfaction, diet, eating disorders and exercise disorders are found in young adults all over the world.Thorough nutrition helps people understand who they are by reassuring them that they are okay without judging or accepting themselves. Social media can positively influence body image in many ways.A healthy body image is important because it affect self-esteem, self-acceptance, and your attitude towards food and exercise.

Keywords: pysical activity, dietary habits, body image, beauty ideals internalization, body appreciation

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Authors: Mehtab Alam

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Sustainable tourism practices require to improve the decreased performance levels in phases of change management for image branding. This paper addresses the innovative approach of using sustainable tourism for image branding as a contemporary tool of foreign policy. The sustainable tourism-based foreign policy promotes cultural values, green tourism, economy, and image management for the avoidance of rising global conflict. The mixed-method approach (quantitative 382 surveys, qualitative 11 interviews at saturation point) implied for the data analysis. The research finding provides the potential of using sustainable tourism by implying skills and knowledge, capacity, and personal factors of change management in improving tourism-based performance levels. It includes the valuable tourism performance role for the success of a foreign policy through sustainable tourism. Change management in tourism-based foreign policy provides the destination readiness for international engagement and curbing of climate issues through green tourism. The research recommends the impact of change management in improving the tourism-based performance levels of image branding for a coercive foreign policy. The paper’s future direction for the immediate implementation of tourism-based foreign policy is to overcome the contemporary issues of travel marketing management, green infrastructure, and cross-border regulation.

Keywords: decrease performance levels, change management, sustainable tourism, image branding, foreign policy

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Authors: Theodora-Venetia Missirli, Konstantina Kyriakopoulou, Magdalini Krokida

Abstract:

Olive mill solid waste is an olive oil mill industry by-product with high phenolic, lipid and organic acid concentrations that can be used as a low cost source of natural antioxidants. In this study, extracts of Olea europaea (olive tree) solid olive mill waste (SOMW) were evaluated in terms of their antiradical activity and total phenolic compounds concentrations, such as oleuropein, hydroxytyrosol etc. SOMW samples were subjected to drying prior to extraction as a pretreatment step. Two drying processes, accelerated solar drying (ASD) and air-drying (AD) (at 35, 50, 70°C constant air velocity of 1 m/s), were applied. Subsequently, three different extraction methods were employed to recover extracts from untreated and dried SOMW samples. The methods include the green Microwave Assisted (MAE) and Ultrasound Assisted Extraction (UAE) and the conventional Soxhlet extraction (SE), using water and methanol as solvents. The efficiency and selectivity of the processes were evaluated in terms of extraction yield. The antioxidant activity (AAR) and the total phenolic content (TPC) of the extracts were evaluated using the DPPH assay and the Folin-Ciocalteu method, respectively. The results showed that bioactive content was significantly affected by the extraction technique and the solvent. Specifically, untreated SOMW samples showed higher performance in the yield for all solvents and higher antioxidant potential and phenolic content in the case of water. UAE extraction method showed greater extraction yields than the MAE method for both untreated and dried leaves regardless of the solvent used. The use of ultrasound and microwave assisted extraction in combination with industrially applied drying methods, such as air and solar drying, was feasible and effective for the recovery of bioactive compounds.

Keywords: antioxidant potential, drying treatment, olive mill pomace, microwave assisted extraction, ultrasound assisted extraction

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