Search results for: multi-phasic liver images

Authors: Magda I. Hassan

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This paper aims to investigate the health effects of aspartame on weanling male hamsters. 20 Golden Syrian hamsters drank only water (control) or water with 6, 11, and 18 mg aspartame/kg of body weight per day for 42 days. Food intake, weight gain, glucose blood level, and lipid profile were determined at the end of the experiment. The animals were sacrificed and histopathological examination of organs (liver, brain and heart) was done. Results revealed that animals in Asp.groups consumed significantly larger amount of food than the control (13.4±5.9, 8.6±2.5 and 8.8±3.0 vs 4.2±2.5 g/day, in succession). Hamsters in the control group showed higher total cholesterol and HDL levels than hamsters in aspartame 6, 11, 18 groups (160±19 vs 101±13, 130±22, 141±15 mg/dl & 144±9 vs 120±12, 118±13, 99±17 respectively (P<0•05)). The control group showed a glucose concentration below those of aspartame groups, indicating no effect of aspartame on glucose blood level. While, there were no significant differences in the triglycerides and LDL levels between control group and Asp.groups. Histopathological changes were observed, especially in brain and liver cells. Aspartame increases appetite and weight gain of young hamsters. Therefore, FDA should reconsider the acceptable daily intake (ADI) of aspartame for children.

Keywords: aspartame, brain, food intake, hamsters

Procedia PDF Downloads 253

Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

Procedia PDF Downloads 161

Authors: Gizaw Mamo Gebeyehu, Marianna Pap, Geza Makkai, Tibor Z. Janosi, Shima Rashidian, Tibor A. Rauch

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Sepsis poses a significant global health threat, necessitating extensive exploration of indicators tied to its pathological mechanisms and multi-organ dysfunction. While murine studies have shed light on sepsis, the intricate cellular and molecular landscape in human sepsis remains enigmatic. Exploring the influence of activated monocyte-derived exosomes in sepsis sheds light on a promising pathway for understanding the intricate cellular and molecular mechanisms involved in this condition in humans. In sepsis, exosome-borne mRNA and miRNA orchestrate immune response gene expression in recipient cells. Yet, the specifics of exosome-mediated cell-to-cell communication, especially how mRNA cargoes modulate gene expression in recipient cells, remain poorly understood. This study aims to elucidate the precise molecular pathways through which exosomal mRNA cargo, particularly MAFB, contributes to the developing sepsis-induced molecular aberrations in liver tissues, employing rigorously defined cell culture conditions. THP-1 cells were treated with LPS to induce changes in exosomal RNA profiles. Exosomes were isolated and characterized using microscopy and mass spectrometry. RNA was extracted from exosomes and sequenced. The most abundant exosomal mRNAs were subjected to GO analysis for functional annotation analysis and KEGG database analysis to identify the involved enriched pathways. PCR (Polymerase Chain Reaction), RNA sequencing, and Western blotting were involved to analyze changes in gene expression, protein levels, and signaling pathways within the liver cells( HepG2) after exposure to exosomal MAFB. This study pinpoints exosomal MAFB as a potential key regulator linked to liver cell damage during sepsis, along with associated genes (miR155HG, H3F3A, and possibly JARD2) forming a crucial molecular pathway contributing to liver cell injury, Together, these elements indicate a vital molecular pathway that plays a significant role in the emergence of liver cell injury during sepsis.. These findings suggest the importance of further research on these components for potential therapeutic interventions in managing acute liver damage in sepsis.

Keywords: sepsis, exososome, exosomal MAFB, LPS-induced THP-1 cells, RNA profiles, sepsis-triggered liver injury

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: Oluwatosin Adetola Arojojoye, Olajumoke Olufunlayo Alao, Philip Odigili

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This study investigated the extent of pollution in Eleyele River in Oyo State, Nigeria by investigating the antioxidant status and malondialdehyde levels (index of lipid peroxidation) in the organs of African Catfish, Clarias gariepinus from the river. Clarias gariepinus weighing between 250g-400g were collected from Eleyele River (a suspected polluted river) and Clarias gariepinus from a clean fish farm (Durantee fisheries) were used as the control. Levels of malondialdehyde, glutathione concentration (GSH) and activities of antioxidant enzymes - superoxide dismutase, catalase and glutathione-S-transferase (GST) were evaluated in the post-mitochondrial fractions of the liver, kidney and gills of the fishes. From the results, there were increases in malondialdehyde level and GSH concentration in the liver, kidney and gills of Clarias gariepinus from Eleyele River when compared with control. Glutathione-S-transferase activity was induced in the liver and kidney of Clarias gariepinus from Eleyele River when compared with control. However, the activity of this enzyme was depleted in the gills of fishes from Eleyele River compared with control. Also there was an induction in SOD activity in the liver of Clarias gariepinus from Eleyele River when compared with control but there was a decrease in the activity of this enzyme in the kidney and gills of fishes from Eleyele River compared with control. Increase in lipid peroxidation and alterations in antioxidant system in Clarias gariepinus from Eleyele River show that the fishes were under oxidative stress. These suggest that the river is polluted probably as a result of industrial, domestic and agricultural wastes frequently discharged into the river. This could pose serious health risks to consumers of water and aquatic organisms from the river.

Keywords: antioxidant, lipid peroxidation, Clarias gariepinus, Eleyele River

Procedia PDF Downloads 497

Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Risti Suryantari, Flaviana

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The aim of this research is to design calibration method of Thermochromic Liquid Crystal for temperature distribution measurement based on mathematical morphology of hue image A glass of water is placed on the surface of sample TLC R25C5W at certain temperature. We use scanner for image acquisition. The true images in RGB format is converted to HSV (hue, saturation, value) by taking of hue without saturation and value. Then the hue images is processed based on mathematical morphology using Matlab2013a software to get better images. There are differences on the final images after processing at each temperature variation based on visualization observation and the statistic value. The value of maximum and mean increase with rising temperature. It could be parameter to identify the temperature of the human body surface like hand or foot surface.

Keywords: thermochromic liquid crystal, TLC, mathematical morphology, hue image

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Authors: Muhammad Waqar Ashraf, Atiq A. Mian

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In the present study, accumulation of eight heavy metals, lead (Pb), cadmium (Cd), manganese (Mn), copper (Cu), zinc (Zn), iron (Fe), nickel (Ni) and chromium (Cr)was determined in kidney, heart, liver and muscle tissues of Lethrinus miniatus fish caught from Arabian Gulf. Metal concentrations in all the samples were measured using Atomic Absorption Spectroscopy. Analytical validation of data was carried out by applying the same digestion procedure to standard reference material (NIST-SRM 1577b bovine liver). Levels of lead (Pb) in the liver tissue (0.60µg/g) exceeded the limit set by European Commission (2005) at 0.30 µg/g. Zinc concentration in all tissue samples were below the maximum permissible limit (50 µg/g) as set by FAO. Maximum mean cadmium concentration was found 0.15 µg/g in the kidney tissues. Highest content of Mn in the studied tissues was seen in the kidney tissue (2.13 µg/g), whereas minimum was found in muscle tissue (0.87 µg/g). The present study led to the conclusion that muscle tissue is the least contaminated tissue in Lethrinus miniatus and consumption of organs should be avoided as much as possible.

Keywords: lethrinus miniatus, arabian gulf, heavy metals, atomic absorption spectroscopy

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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Authors: Turan Yaman, Zabit Yener, Ismail Celik

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The aim of this study was to investigate the antioxidant properties and protective role of honey, considered a part of traditional medicine, against carcinogen chemical aflatoxin (AF) exposure in rats, which were evaluated by histopathological changes in liver and kidney, measuring level of serum marker enzymes [aspartate aminotransferase (AST), alanin aminotransferase (ALT), gamma glutamil transpeptidase (GGT)], antioxidant defense systems [Reduced glutathione (GSH), glutathione reductase (GR), superoxide dismutase (SOD), glutathione-S-transferase (GST) and catalase (CAT)], and lipid peroxidation content in liver, erythrocyte, brain, kidney, heart and lungs. For this purpose, a total of eighteen healthy Sprague-Dawley rats were randomly allocated into three experimental groups: A (Control), B (AF-treated) and C (AF+honey-treated). While rats in group A were fed with a diet without AF, B, and C groups received 25 µg of AF/rat/day, where C group additionally received 1 mL/kg of honey by gavage for 90 days. At the end of the 90-day experimental period, we found that the honey supplementation decreased the lipid peroxidation and the levels of enzyme associated with liver damage, increased enzymatic and non-enzymatic antioxidants in the AF+honey-treated rats. Hepatoprotective and nephroprotective effects of honey is further substantiated by showing almost normal histological architecture in AF+honey-treated group, compared to degenerative changes in the liver and kidney of AF-treated rats. Additionally, honey supplementation ameliorated antioxidant defense systems and lipid peroxidation content in other tissues of AF+honey-treated rats. In conclusion, the present study indicates that honey has a hepatoprotective and nephroprotective effect in rats with experimental aflatoxicosis due to its antioxidant activity.

Keywords: aflatoxicosis, honey, histopathology, malondialdehyde, antioxidant, rat

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Authors: Luciano Tarantino, Emanuele Balzano, Aurelio Nasto

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S.R. 53 years. January 2009: HCV-related cirrhosis, Child-Pugh A5 class, EGDS no aesophageal Varices. No important comorbidities. Treated with PEG-IFN+Ribavirin (march-november 2009) with subsequent sustained virologic response. HCVRNA absent overtime. October 2016 :CT detected small HCC nodule in the VIII segment (diam.=12 mm). Treated with US guided RF-ablation. November 2016 CT: complete necrosis. Unfortunately, the patient dropped out US and CT follow-up controls.September 2018: asthenia and weight loss. CT showed a large tumor infiltrating V-VII-VI segments and complete PVTT of right portal vein and its branches . Surgical Consultation excluded indication to Liver resection and OLT . 23 october 2018: ECT of a large peri-hilar area of the tumor including the PVTT. 1 and 3 months post-treatment CT showed complete necrosis and retraction of the thrombus and residual viable tumor in the peripheral portion of the right lobe . Therefor, the patient was reevaluated for OLT and considered eligible in waiting list . March 2019: CT showed no perihilar or portal vein recurrence and distant progression in the right lobe . March 2019 : Trans-arterial-Radio-therapy (TARE) of the right lobe. Post-treatment CT demonstrated no perihilar or portal vein recurrence and extensive necrosis of the residual tumor . December 2019: CT demonstrated several recurrences of HCC infiltrating the VI and VII segment . Howewer no recurrence was observed at hepatic hilum and in portal vessels . Therefore, on February 2020 the patient received OLT. At 44 months follow-up, no complication or recurrence or liver disfunction have been observed.

Keywords: hepatocellular carcinoma, portal vein tumor thrombosis, interventional ultrasound, liver tumor ablation, liver transplantation

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Authors: Muhammad Waqar Ashraf

Abstract:

In the present study, accumulation of eight heavy metals, lead (Pb), cadmium (Cd), manganese (Mn), copper (Cu), zinc (Zn), iron (Fe), nickel (Ni) and chromium (Cr)was determined in kidney, heart, liver and muscle tissues of Lethrinus Miniatus fish caught from Arabian Gulf. Metal concentrations in all the samples were measured using Graphite Furnace Atomic Absorption Spectroscopy (GF-AAS). Analytical validation of data was carried out by applying the same digestion procedure to standard reference material (NIST-SRM 1577b bovine liver). Levels of lead (Pb) in the liver tissue (0.60µg/g) exceeded the limit set by European Commission (2005) at 0.30 µg/g. Zinc concentration in all tissue samples were below the maximum permissible limit (50 µg/g) as set by FAO. Maximum mean cadmium concentration was found to be 0.15 µg/g in the kidney tissues. Highest content of Mn in the studied tissues was seen in the kidney tissue (2.13 µg/g), whereas minimum was found in muscle tissue (0.87 µg/g). The present study led to the conclusion that muscle tissue is the least contaminated tissue in Lethrinus Miniatus and consumption of organs should be avoided as much as possible.

Keywords: Arabian gulf, Lethrinus miniatus, heavy metals, atomic absorption spectroscopy

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Mohammed A. Arishy, Sultan M. Alharbi, Mohammed A. Hakami, Farid M. Abualsail, Mohammad A. Attafi, Riyadh M. Tobaiqi, Hussain M. Alsalem, Ibraheem M. Attafi

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Lidocaine is the most common local anesthetics used for para cervical block to reduce pain associated with surgical abortion. A 25-year-old pregnant woman who. She died before reaching hospital, and she was undergoing criminal abortion during the first trimester. In post-mortem investigations and autopsy shows no clear finding; therefore, toxic substances must be suspected and searched for routinely toxicology analysis. In this case report, the postmortem concentration of lidocaine was detected blood, brain, liver, kidney, and stomach. For lidocaine identification and quantification, sample was extracted using solid phase extraction and analyzed by GC-MS (Shimadzu, Japan). Initial screening and confirmatory analysis results showed that only lidocaine was detected in all collected samples, and no other toxic substances or alcohol were detected. The concentrations of lidocaine in samples were 19, 17, 14, 7, and 3 ug/m in the brain, blood, kidney, liver, and stomach, respectively. Lidocaine blood concentration (17 ug/ml) was toxic level and may result in death. Among the tissues, brain showed the highest level of lidocaine, followed by the kidney, liver, and stomach.

Keywords: forensic toxicology, GC-MS, lidocaine, postmortem

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Zakia Alioua, Amira Soumia, Zerouali-Khodja Fatiha

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In spite of a wide variety of contaminants such as heavy metals and organic compounds in addition to the importance of extended pollution, the deep-sea and its species are not in haven and being affected through contaminants exposure. This investigation is performed in order to provide data on the presence of pathological changes in the liver and gonads of the greater forkbeard. A total of 998 specimens of the teleost fish Phycis blennoides Brünnich, 1768 ranged from 5,7 to 62,7 cm in total length, were obtained from the commercial fisheries of Algerian ports. The sampling has been carried out monthly from December 2013 to June 2015 and from January to June 2016 caught by trawlers and longlines between 75 and 600 fathoms in the coast of Algeria. Individuals were sexed their gonads, and their livers were removed and processed for light microscopy and one case of atresia was identified. In whole, overall 0,002% of the specimens presented some degree of liver steatosis. For the gastric section, 442 selected stomachs contents were observed looking for parasitic infestation and enumerate 212 nematodes. A prospecting survey for metal contaminant was performed on the liver by atomic absorption spectrophotometry analysis.

Keywords: atresia, coast of Algeria, histopathology, nematode, Phycis blennoides, steatosis

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Authors: Moein Izadi, Ali Mohammadzadeh

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Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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Authors: Marija Lončar, Zorana Šuljug Vučica, Magdalena Nigoević

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Diverse social, cultural and economic trends and changes in contemporary societies influence the ways masculinity is represented in a variety of media. Masculinity is constructed within media images as a dynamic process that changes slowly over time and is shaped by various social factors. In many societies, dominant masculinity is still associated with authority, heterosexuality, marriage, professional and financial success, ethnic dominance and physical strength. But contemporary media depict men in ways that suggest a change in the approach to media images. The number of media images of men, which promote men’s identity through their body, have increased. With the male body more scrutinized and commodified, it is necessary to highlight how the body is represented and which visual elements are crucial since the body has an important role in the construction of masculinities. The study includes content analysis of male body images in the advertisements of different men’s and women’s lifestyle magazines available in Croatia. The main aim was to explore how masculinities are currently being portrayed through body regarding age, physical appearance, fashion, touch and gaze. The findings are also discussed in relation to female images since women are central in many of the processes constructing masculinities and according to the recent conceptualization of masculinity. Although the construction of male images varies through body features, almost all of them convey the message that men’s identity could be managed through manipulation and by enhancing the appearance. Furthermore, they suggest that men should engage in “bodywork” through advertised products, activities and/or practices, in order to achieve their preferred social image.

Keywords: body images, content analysis, lifestyle magazines, masculinity

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Ahad Salimi, Hassan Masoumi

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Prostate cancer is one of the most common recognized cancers in men, and, is one of the most important mortality factors of cancer in this group. Determining of prostate’s boundary in TRUS (Transrectal Ultra Sound) images is very necessary for prostate cancer treatments. The weakness edges and speckle noise make the ultrasound images inherently to segment. In this paper a new automatic algorithm for prostate segmentation in TRUS images proposed that include three main stages. At first morphological smoothing and sticks filtering are used for noise removing. In second step, for finding a point in prostate region, SOFM algorithm is enlisted and in the last step, the boundary of prostate extracting accompanying active contour is employed. For validation of proposed method, a number of experiments are conducted. The results obtained by our algorithm show the promise of the proposed algorithm.

Keywords: SOFM, preprocessing, GVF contour, segmentation

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Authors: Justie Su-Tzu Juan, Ming-Jheng Li, Ching-Fen Lee, Ruei-Yu Wu

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A secret image sharing scheme is a way to protect images. The main idea is dispersing the secret image into numerous shadow images. A secret image sharing scheme can withstand the impersonal attack and achieve the highly practical property of multiuse  is more practical. Therefore, this paper proposes a verifiable and detectable secret image-sharing scheme called VDGMSISS to solve the impersonal attack and to achieve some properties such as encrypting multi-secret images at one time and multi-use. Moreover, our scheme can also be used for any genera access structure.

Keywords: multi-secret image sharing scheme, verifiable, de-tectable, general access structure

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Authors: Tzu-Hao Li, Shie-Liang Hsieh, Han-Chieh Lin, Ying-Ying Yang

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TNF superfamily-stimulated pathogenic cascades and macrophage (M1)/kupffer cells (KC) polarization are important in the pathogenesis of ischemia-reperfusion (IR) liver injury in animals with hepatic steatosis (HS). Decoy receptor 3 (DcR3) is a common upstream inhibitor of the above-mentioned pathogenic cascades. The study evaluated whether modulation of these DcR3-related cascades was able to protect steatotic liver from IR injury. Serum and hepatic DcR3 levels were lower in patients and animals with HS. Accordingly, the effects of pharmacologic and genetic DcR3 replacement on the IR-related pathogenic changes were measured. Significantly, DcR3 replacement protected IR-Zucker(HS) rats and IR-DcR3-Tg(HS) mice from IR liver injury. The beneficial effects of DcR3 replacement were accompanied by decreased serum/hepatic TNF, soluble TNF-like cytokine 1A (TL1A), Fas ligand (Fas-L) and LIGHT, T-helper-cell-1 cytokine (INF) levels, neutrophil infiltration, M1 polarization, neutrophil-macrophage/KC-T-cell interaction, hepatocyte apoptosis and improved hepatic microcirculatory failure among animals with IR-injured steatotic livers. Additionally, TL1A, Fas-L, LIGHT and TLR4/NFB signals were found to mediate the DcR3-related protective effects of steatotic livers from IR injury. Using multimodal in vivo and in vitro approaches, we found that DcR3 was a potential agent to protect steatotic livers from IR injury by simultaneous blocking the multiple IR injury-related pathogenic changes.

Keywords: Decoy 3 receptor, ischemia-reperfusion injury, M1 polarization, TNF superfamily

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Authors: Ilia Zharikov, Philipp Nikitin, Ilia Vasiliev, Vladimir Dokholyan

Abstract:

With the increasing popularity of document analysis and recognition systems, text detection (TD) and optical character recognition (OCR) in document images become challenging tasks. However, according to our best knowledge, no publicly available datasets for these particular problems exist. In this paper, we introduce a Distorted Document Images dataset (DDI-100) and provide a detailed analysis of the DDI-100 in its current state. To create the dataset we collected 7000 unique document pages, and extend it by applying different types of distortions and geometric transformations. In total, DDI-100 contains more than 100,000 document images together with binary text masks, text and character locations in terms of bounding boxes. We also present an analysis of several state-of-the-art TD and OCR approaches on the presented dataset. Lastly, we demonstrate the usefulness of DDI-100 to improve accuracy and stability of the considered TD and OCR models.

Keywords: document analysis, open dataset, optical character recognition, text detection

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Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

Abstract:

Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

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Authors: Mostafa Jafari

Abstract:

How the people continually create and recreate the six dimensional inter- sub-cultural relationships from the strategic point of view? Can they engineer and direct it toward creating a set of peaceful subcultures? This paper answers to these questions. Our mental images shape the quantity and quality of our relationships. The six dimensions of mental images are: my mental image about myself, your mental image about yourself, my mental image about you, your mental image about me, my imagination about your image about me and your imagination about my mental image about you. Strategic engineering is dynamically shaping these images and imaginations.Methodology: This survey, which is based on object and the relation between the variables, is explanatory, correlative and quantitative. The target community members are 90 educated people from universities. The data has been collected through questionnaire and interview and has been analyzed by descriptive statistical techniques and qualitative method. Results: Our findings show that engineering and deliberatly managing the process of inter- sub-cultural transactions in the national and global level can enable us to continually reform a peaceful set of learner sub-culturals toward recreate a peaceful unit global Home.

Keywords: strategic engineering, mental image, six dimensional mental images strategy , cultural literacy, radar technique

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Authors: Sukumar Namineni, Tracy O'Connor, Ulrich Kalinke, Percy Knolle, Mathias Heikenwaelder

Abstract:

The liver is one of the pivotal organs in vertebrate animals, serving a multitude of functions such as metabolism, detoxification and protein synthesis and including a predominant role in innate immunity. The innate immune mechanisms pertaining to liver in controlling viral infections have largely been attributed to the Kupffer cells, the locally resident macrophages. However, all the cells of liver are equipped with innate immune functions including, in particular, the hepatocytes. Hence, our aim in this study was to elucidate the innate immune contribution of hepatocytes in viral clearance using mice lacking Ikkβ specifically in the hepatocytes, termed IkkβΔᴴᵉᵖ mice. Blockade of Ikkβ activation in IkkβΔᴴᵉᵖ mice affects the downstream signaling of canonical NF-κB signaling by preventing the nuclear translocation of NF-κB, an important step required for the initiation of innate immune responses. Interestingly, infection of IkkβΔᴴᵉᵖ mice with lymphocytic choriomeningitis virus (LCMV) led to strongly increased hepatic viral titers – mainly confined in clusters of infected hepatocytes. This was due to reduced interferon stimulated gene (ISG) expression during the onset of infection and a reduced CD8+ T-cell-mediated response. Decreased ISG production correlated with increased liver LCMV protein and LCMV in isolated hepatocytes from IkkβΔᴴᵉᵖ mice. A similar phenotype was found in LCMV-infected mice lacking interferon signaling in hepatocytes (IFNARΔᴴᵉᵖ) suggesting a link between NFkB and interferon signaling in hepatocytes. We also observed a failure of interferon-mediated inhibition of HBV replication in HepaRG cells treated with NF-kB inhibitors corroborating our initial findings with LCMV infections. Collectively, these results clearly highlight a previously unknown and influential role of hepatocytes in the induction of innate immune responses leading to viral clearance during a systemic viral infection with LCMV-WE.

Keywords: CD8+ T cell responses, innate immune mechanisms in the liver, interferon signaling, interferon stimulated genes, NF-kB signaling, viral clearance

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Authors: M. Abuqebitah, H. Tanyildizi, N. Yeyin, I. Cavdar, M. Demir, L. Kabasakal

Abstract:

Aim: Targeted radionuclide therapy (TRT) is an increasingly used treatment modality for wide range of cancers. Presently dosimetry is highly required either to plan treatment or to ascertain the absorbed dose delivered to critical organs during treatment. Methods and Materials: The study comprised 7 patients suffered from prostate cancer with progressive disease and candidate to undergo Lu-177-DOTA-617 therapy following to PSMA- PET/CT imaging for all patients. (5.2±0.3 mCi) was intravenously injected. To evaluate bone marrow absorbed dose 2 cc blood samples were withdrawn in short variable times (3, 15, 30, 60, 180 minutes) after injection. Furthermore, whole body scans were performed using scintillation gama camera in 4, 24, 48, and 120 hours after injection and in order to quantify the activity taken up in the body, kidneys , liver, right parotid, and left parotid the geometric mean of anterior and posterior counts were determined through ROI analysis, after that background subtraction and attenuation correction were applied using patients PSMA- PET/CT images taking in a consideration: organ thickness, body thickness, and Hounsfield unites from CT scan. OLINDA/EXM dosimetry program was used for curve fitting, residence time calculation, and absorbed dose calculations. Findings: Absorbed doses of bone marrow, left kidney, right kidney, liver, left parotid, right parotid, total body were 1.28±0.52, 32.36±16.36, 32.7±13.68, 10.35±3.45, 38.67±21.29, 37.55±19.77, 2.25±0.95 (mGy/mCi), respectively. Conclusion: Our first results clarify that Lu-177-DOTA-617 is safe and reliable therapy as there were no complications seen. In the other hand, the observable variation in the absorbed dose of the critical organs among the patients necessitate patient-specific dosimetry approach to save body organs and particularly highly exposed kidneys and parotid gland.

Keywords: Lu-177-PSMA, prostate cancer, radionuclide therapy

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