Search results for: lung parenchyma segmentation

Authors: M. G. Talasbayen, N. N. Dyussenbayev, Y. D. Kali, R. A. Zholbarysov, Y. N. Duissenbayev, I. Z. Mammadinova, S. M. Nuradilov

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Background. Hemorrhagic stroke is an acute cerebrovascular accident resulting from rupture of a cerebral vessel or increased permeability of the wall and imbibition of blood into the brain parenchyma. Arterial hypertension is a common cause of hemorrhagic stroke. Male gender and age over 55 years is a risk factor for intracerebral hemorrhage. Treatment of intracerebral hemorrhage is aimed at the primary pathophysiological link: the relief of coagulopathy and the control of arterial hypertension. Early surgical treatment can limit cerebral compression; prevent toxic effects of blood to the brain parenchyma. Despite progress in the development of neuroimaging data, the use of minimally invasive techniques, and navigation system, mortality from intracerebral hemorrhage remains high. Materials and methods. The study included 78 patients (62.82% male and 37.18% female) with a verified diagnosis of hemorrhagic stroke in the period from 2019 to 2021. The age of patients ranged from 25 to 80 years, the average age was 54.66±11.9 years. Demographic, brain CT data (localization, volume of hematomas), methods of treatment, and disease outcome were analyzed. Results. The retrospective analyze demonstrate that 78.2% of all patients underwent surgical treatment: decompressive craniectomy in 37.7%, craniotomy with hematoma evacuation in 29.5%, and hematoma draining in 24.59% cases. The study of the proportion of deaths, depending on the volume of intracerebral hemorrhage, shows that the number of deaths was higher in the group with a hematoma volume of more than 60 ml. Evaluation of the relationship between the time before surgery and mortality demonstrates that the most favorable outcome is observed during surgical treatment in the interval from 3 to 24 hours. Mortality depending on age did not reveal a significant difference between age groups. An analysis of the impact of the surgery type on mortality reveals that decompressive craniectomy with or without hematoma evacuation led to an unfavorable outcome in 73.9% of cases, while craniotomy with hematoma evacuation and drainage led to mortality only in 28.82% cases. Conclusion. Even though the multimodal approaches, the development of surgical techniques and equipment, and the selection of optimal conservative therapy, the question of determining the tactics of managing and treating hemorrhagic strokes is still controversial. Nevertheless, our experience shows that surgical intervention within 24 hours from the moment of admission and craniotomy with hematoma evacuation improves the prognosis of treatment outcomes.

Keywords: hemorragic stroke, Intracerebral hemorrhage, surgical treatment, stroke mortality

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Authors: Abobaker Abrahem M. Saad, Asma Abudasalam

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The stem node segments were cultured on Murashige and Skoog (MS) medium. In the case of using MS+ Zeatin (1 mg/l), small shoot buds were formed directly in 70% of explants after 15 days, their length range between 0.1 to 0.3 cm after two weeks and reached 0.3 cm in length and three shoots in numbers after 4 weeks. When those small shoots were sub cultured on the same medium, they increased in length, number and reached 0.4 cm with 4 shoots, 0.4 cm with 5 shoots after six, eight and ten weeks respectively. In the case of using MS free hormones, MS+IAA (0.2mg/l) +BA (0.5mg/l), MS + kin(0.5mg/l), MS + kin (3mg/l) and MS +NAA (3mg/l) +BA (1mg/l), no sign of responses were noticed and only change in color in some cases. Different types of parenchyma cells and many layers of thick wall sclerenchyma cells were observed on MS+BA (1mg/l).

Keywords: Maerua, stem node, shoots, buds, In vitro

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Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: S. Mamoucha, J. Rahul, N. Christodoulakis

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Introduction: Nature has been the source of medicinal agents since the dawn of the human existence on Earth. Currently, millions of people, in the developing world, rely on medicinal plants for primary health care, income generation and lifespan improvement. In Greece, more than 5500 plant taxa are reported while about 250 of them are considered to be of great pharmaceutical importance. Among the plants used for medical purposes, Vitex agnus-castus L. (Verbenaceae) is known since ancient times. It is a small tree or shrub, widely distributed in the Mediterranean basin up to the Central Asia. It is also known as chaste tree or monks pepper. Theophrastus mentioned the shrub several times, as ‘agnos’ in his ‘Enquiry into Plants’. Dioscorides mentioned the use of V. agnus-castus for the stimulation of lactation in nursing mothers and the treatment of several female disorders. The plant has important medicinal properties and a long tradition in folk medicine as an antimicrobial, diuretic, digestive and insecticidal agent. Materials and methods: Leaves were cleaned, detached, fixed, sectioned and investigated with light and Scanning Electron Microscopy (SEM). Histochemical tests were executed as well. Specific histochemical reagents (osmium tetroxide, H2SO4, vanillin/HCl, antimony trichloride, Wagner’ s reagent, Dittmar’ s reagent, potassium bichromate, nitroso reaction, ferric chloride and di methoxy benzaldehyde) were used for the sub cellular localization of secondary metabolites. Results: Light microscopical investigations of the elongated leaves of V. agnus-castus revealed three layers of palisade parenchyma, just below the single layered adaxial epidermis. The spongy parenchyma is rather loose. Adaxial epidermal cells are larger in magnitude, compared to those of the abaxial epidermis. Four different types of capitate, secreting trichomes, were localized among the abaxial epidermal cells. Stomata were observed at the abaxial epidermis as well. SEM revealed the interesting arrangement of trichomes. Histochemical treatment on fresh and plastic embedded tissue sections revealed the nature and the sites of secondary metabolites accumulation (flavonoids, steroids, terpenes). Acknowledgment: This work was supported by IKY - State Scholarship Foundation, Athens, Greece.

Keywords: Vitex agnus-castus, leaf anatomy, histochemical reagents, secondary metabolites

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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Authors: Ram Sharan Mehta

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The number of new cancer cases annually is estimated to rise from 10.9 million in 2002 to more than 16 million by 2020, if current trends continue. Much of this increase in absolute numbers derives from the ageing of populations worldwide. The objectives of this study were to find out the demographic characteristics of the admitted cancer patients in BPKIHS. It was hospital based descriptive cross-sectional study conducted reviewing all the records of admitted diagnosed cancer patients in BPKIHS from 15th October 2004 to 14th October 2012. Using total enumerative sampling technique all 1379 diagnosed cancer patients record were reviewed after obtaining the permission from concerned authorities. Using SPSS-15 software package data was analyzed. It was found that majority (71%) of cancer patients were of age more than 40 years and equal of both sexes. Most of the clients were form Sunsari (31.1%), Morang (16.6%) and Jhapa (17%) districts. The mean hospitalization day is 8.32 and very few patients (5.2%) were only cured. The numbers of cancer patients are markedly increases in BPKIHS, especially in advanced stage. It is mandatory to start the cancer information and education programme in eastern region of Nepal and proper management of cancer patients using chemotherapy, radiotherapy and surgery at BPKIHS for quality patient care.

Keywords: lung, cancer, patients, Nepal

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Hamza Hadj Abdallah, Brahim Belabdi

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Respiratory disease is a dominant pathology in cattle. It causes mortality and especially morbidity and irreversible damage. Although the dairy herd is affected, it is essentially the lactating herd and especially young cattle either nursing or fattening that undergo the greatest economic impact. The objective of this study is to establish a microbiological diagnosis of bovine respiratory inffections from lung presented with gross lesions at the slaughter of Batna. A total of 124 samples (pharyngeal and nasal swabs and lung fragments) from 31 seven months old calves, with lung lesions was collected to determine possible correlations between etiologic agents and lesion types. The hépatisation injury (or consolidation) was the major lesion (45.17%) preferentially localized in the right apical lobe. A diverse microbial flora (15 genera and 291 strains was isolated. The bacteria most frequently isolated are the Enterobacteriaceae (49.45%), Staphylococci (25.1%) followed by non Enterobacteriaceae bacilli represented by Pseudomonas (5.83%) and finally, Streptococcus (13.38 %). The pneumotropic bacteria (Pasteurellaaerogenes and Pasteurellapneumotropica) were isolated at a rate of 0.68%. The study of the sensitivity of some germs to antibiotics showed a sensitivity of 100% for ceftazidime. A very high sensitivity was also observed for kanamycin, Ciprofloxacin, Imepinem, Cefepime, Tobramycin and Gentamycin (between 90% and 97%). Strains of E. coli showed a sensitivity of 100% for Imepinem, while only 55.9% of the strains were sensitive to Ampicillin. The isolated Pasteurella exhibited excellent sensitivity (100%) for the antimicrobials used with the exception of Colistin and Ticarcillin-Clavulanic acid association which showed a sensitivity of 50%.This survey has demonstrated the strong spread of atypical pneumonia in cattle population (bulls) at the slaughterhouse of Batna justifying stunting and losses in cattle farms in the region.Thus, it was considered urgent to establish a profile of sensitivity of different germs to antibiotics isolated to limit this increasingly dreadful infection.

Keywords: Pasteurella, enterobacteria, bacteriology, pneumonia

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Authors: Farzaneh Ziaee, Mohammad Ziaee

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N-acetyl-L-cysteine (NAC) is a well-known mucolytic agent, and recently its efficacy has been examined for the prevention and remediation of several diseases such as lung infections caused by Coronavirus. Also, it is administrated as the main antidote in paracetamol overdose and is effective for the treatment of idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD). This medicine is used as an antioxidant to prevent diabetic kidney disease (nephropathy). In this study, a method for the acylation of amino acids is employed to manufacture this drug in a height yield. Regarding this patented path, NAC can be made in a single batch step at ambient pressure and temperature. Moreover, this study offers a technique to make peptide bonds which is of interest for pharmaceutical and medicinal industries. The separation process was undertaken using appropriate solvents to achieve an excellent purification level. The synthesized drug was characterized via proton nuclear magnetic resonance (1H NMR), high-performance liquid chromatography (HPLC), Fourier transform infrared spectroscopy (FT-IR), elemental analysis, and melting point.

Keywords: N-acetylcysteine, synthesis, mucolytic medication, lung anti-inflammatory, COVID-19, antioxidant, pharmaceutical supplement, characterization

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Authors: P. Jost, L. Muckova, M. Matula, J. Pejchal, D. Jun, R. Stetina

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Sulfur mustard (bis(2-chlorethyl) sulfide) is highly toxic, chemical warfare agent that has been used in the past in several armed conflicts. Except for the skin, respiratory tract is one of the important routes of exposure. The elucidation and understanding of the mechanism of toxicity of SM have been effort intensive research. The multiple targets character of SM caused cellular damage resulted in activation of many different mechanisms which contribute to cellular response and participate in the final cytopathology effect. In our present work, we compared time-dependent changes in sulfur mustard exposed adult human lung fibroblasts NHLF and lung epithelial alveolar cell line A-549. Cell viability (MTT assay, Calcein-AM assay, and xCELLigence - real-time cell analysis), apoptosis (flow cytometry), mitochondrial membrane potential (Δψm, flow cytometry), reactive oxygen species induction (DC and cell cycle distribution (flow cytometry) were studied. We observed significantly decreased mitochondrial membrane potential and subsequent induction of apoptosis correlating with decreased cellular viability in the sulfur mustard exposed cells. In low concentrations, sulfur mustard-induced S-phase cell cycle arrest, on the other hand, high concentrations, cell cycle phase distribution of sulfur mustard exposed cells resembled cell cycle phase distribution of control group, which implies nonspecific cell cycle inhibition. Epithelial cells A-549 was found as more sensible to sulfur mustard toxicity. Acknowledgements: This work was supported by a long-term organization development plan Medical Aspects of Weapons of Mass Destruction of the Faculty of Military Health Sciences, University of Defence.

Keywords: apoptosis, cell cycle, cytotoxicity, sulfur mustard

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: Abul B. M. M. K. Islam, Mandar Dave, Roderick V. Jensen, Ashok R. Amin

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A systems approach was applied to characterize differentially expressed transcripts, bioinformatics pathways, and proteins and prostaglandins (PGs) from lung fibroblasts procured from wild-type (WT), COX-1-/- and COX-2-/- mice to understand system level control mechanism. Bioinformatics analysis of COX-2 and COX-1 ablated cells induced COX-1 and COX-2 specific signature respectively, which significantly overlapped with an 'IL-1β induced inflammatory signature'. This defined novel cross-talk signals that orchestrated coordinated activation of pathways of sterile inflammation sensed by cellular stress. The overlapping signals showed significant over-representation of shared pathways for interferon y and immune responses, T cell functions, NOD, and toll-like receptor signaling. Gene Ontology Biological Process (GOBP) and pathway enrichment analysis specifically showed an increase in mRNA expression associated with: (a) organ development and homeostasis in COX-1-/- cells and (b) oxidative stress and response, spliceosomes and proteasomes activity, mTOR and p53 signaling in COX-2-/- cells. COX-1 and COX-2 showed signs of functional pathways committed to cell cycle and DNA replication at the genomics level. As compared to WT, metabolomics analysis revealed a significant increase in COX-1 mRNA and synthesis of basal levels of eicosanoids (PGE2, PGD2, TXB2, LTB4, PGF1α, and PGF2α) in COX-2 ablated cells and increase in synthesis of PGE2, and PGF1α in COX-1 null cells. There was a compensation of PGE2 and PGF1α in COX-1-/- and COX-2-/- cells. Collectively, these results support a broader, differential and collaborative regulation of both COX-1 and COX-2 pathways at the metabolic, signaling, and genomics levels in cellular homeostasis and sterile inflammation induced by cellular stress.

Keywords: cyclooxygenases, inflammation, lung fibroblasts, systemic

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Authors: Flaurence Benjamain, Michel Casperance

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We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

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This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

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Authors: Elsie M. Nolte, Annie M. Joubert, Roy Lakier, Maryke Etsebeth, Jolene M. Helena, Marcel Verwey, Laurence Lafanechere, Anne E. Theron

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Treatment regimens for breast- and lung cancers may include both radiation- and chemotherapy. Ideally, a pharmaceutical agent which selectively sensitizes cancer cells to gamma (γ)-radiation would allow administration of lower doses of each modality, yielding synergistic anti-cancer benefits and lower metastasis occurrence, in addition to decreasing the side-effect profiles. A range of 2-methoxyestradiol (2-ME) analogues, namely 2-ethyl-3-O-sulphamoyl-estra-1,3,5 (10) 15-tetraene-3-ol-17one (ESE-15-one), 2-ethyl-3-O-sulphamoyl-estra-1,3,5(10),15-tetraen-17-ol (ESE-15-ol) and 2-ethyl-3-O-sulphamoyl-estra-1,3,5(10)16-tetraene (ESE-16) were in silico-designed by our laboratory, with the aim of improving the parent compound’s bioavailability in vivo. The main effect of these compounds is the disruption of microtubule dynamics with a resultant mitotic accumulation and induction of programmed cell death in various cancer cell lines. This in vitro study aimed to determine the cellular responses involved in the radiation sensitization effects of these analogues at low doses in breast- and lung cancer cell lines. The oestrogen receptor positive MCF-7-, oestrogen receptor negative MDA-MB-231- and triple negative BT-20 breast cancer cell lines as well as the A549 lung cancer cell line were used. The minimal compound- and radiation doses able to induce apoptosis were determined using annexin-V and cell cycle progression markers. These doses (cell line dependent) were used to pre-sensitize the cancer cells 24 hours prior to 6 gray (Gy) radiation. Experiments were conducted on samples exposed to the individual- as well as the combination treatment conditions in order to determine whether the combination treatment yielded an additive cell death response. Morphological studies included light-, fluorescence- and transmission electron microscopy. Apoptosis induction was determined by flow cytometry employing annexin V, cell cycle analysis, B-cell lymphoma 2 (Bcl-2) signalling, as well as reactive oxygen species (ROS) production. Clonogenic studies were performed by allowing colony formation for 10 days post radiation. Deoxyribonucleic acid (DNA) damage was quantified via γ-H2AX foci and micronuclei quantification. Amplification of the p53 signalling pathway was determined by western blot. Results indicated that exposing breast- and lung cancer cells to nanomolar concentrations of these analogues 24 hours prior to γ-radiation induced more cell death than the compound- and radiation treatments alone. Hypercondensed chromatin, decreased cell density, a damaged cytoskeleton and an increase in apoptotic body formation were observed in cells exposed to the combination treatment condition. An increased number of cells present in the sub-G1 phase as well as increased annexin-V staining, elevation of ROS formation and decreased Bcl-2 signalling confirmed the additive effect of the combination treatment. In addition, colony formation decreased significantly. p53 signalling pathways were significantly amplified in cells exposed to the analogues 24 hours prior to radiation, as was the amount of DNA damage. In conclusion, our results indicated that pre-treatment of breast- and lung cancer cells with low doses of 2-ME analogues sensitized breast- and lung cancer cells to γ-radiation and induced apoptosis more so than the individual treatments alone. Future studies will focus on the effect of the combination treatment on non-malignant cellular counterparts.

Keywords: cancer, microtubule dynamics, radiation therapy, radiosensitization

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Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

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Authors: Ya-Ting Chuang, Krystle Leung, Ya-Jen Chang, Rosemarie H. DeKruyff, Paul B. Savage, Richard Cruse, Christophe Benoit, Dirk Elewaut, Nicole Baumgarth, Dale T. Umetsu

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We examined characteristics of a Natural Killer T (NKT) cell subpopulation that developed during influenza infection in neonatal mice, and that suppressed the subsequent development of allergic asthma in a mouse model. This NKT cell subset expressed CD38 but not CD4, produced IFN-γ, but not IL-17, IL-4 or IL-13, and inhibited the development of airway hyperreactivity (AHR) through contact-dependent suppressive activity against helper CD4 T cells. The NKT subset expanded in the lungs of neonatal mice after infection with influenza, but also after treatment of neonatal mice with a Th1-biasing α-GalCer glycolipid analogue, Nu-α-GalCer. These results suggest that early/neonatal exposure to infection or to antigenic challenge can affect subsequent lung immunity by altering the profile of cells residing in the lung and that some subsets of NKT cells can have direct inhibitory activity against CD4+ T cells in allergic asthma. Importantly, our results also suggest a potential therapy for young children that might provide protection against the development of asthma.

Keywords: NKT subset, asthma, airway hyperreactivity, hygiene hypothesis, influenza

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Authors: Thusitha Mabotuwana, Christopher S. Hall

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Radiologists routinely make follow-up imaging recommendations, usually based on established clinical practice guidelines, such as the Fleischner Society guidelines for managing lung nodules. In order to ensure optimal care, it is important to make guideline-compliant recommendations, and also for patients to follow-up on these imaging recommendations in a timely manner. However, determining such compliance rates after a specific finding has been observed usually requires many time-consuming manual steps. To address some of these limitations with current approaches, in this paper we discuss a methodology to automatically detect finding-specific follow-up recommendations from radiology reports and create a visualization for relevant subsequent exams showing the modality transitions. Nearly 5% of patients who had a lung related follow-up recommendation continued to have at least eight subsequent outpatient CT exams during a seven year period following the recommendation. Radiologist and section chiefs can use the proposed tool to better understand how a specific patient population is being managed, identify possible deviations from established guideline recommendations and have a patient-specific graphical representation of the imaging pathways for an abstract view of the overall treatment path thus far.

Keywords: follow-up recommendations, follow-up tracking, care pathways, imaging pathway visualization

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Authors: Karthikeyan M., Paul M. J.

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This abstract describes a case of central pancreatectomy (CP) for a 50-year-old woman with a neuroendocrine tumor in the mid-body of the pancreas. CP, a parenchyma-sparing surgical option, preserves the distal pancreas and spleen, reducing the risk of pancreatic endocrine and exocrine insufficiency compared to traditional resections. The patient, initially misdiagnosed with transient ischemic attack, presented with hypoglycemic symptoms and was found to have a pancreatic lesion. Post-operative results were positive, with a reduction in pancreatic drain volume and normalization of blood sugar levels. This case highlights CP's efficacy in treating centrally located pancreatic lesions while maintaining pancreatic function.

Keywords: central pancreatectomy without anastomosis, no endocrine deficiency on follow-op, less post-op hospital stay, less post-op complications

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Abdulkader Helwan

Abstract:

Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Anshika Kankane, Dongshik Kang

Abstract:

Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Shahab Azimi, Siamak Arzanpour, Anahita Sayyar

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Asthma and Chronic obstructive pulmonary disease (COPD) are common lung diseases that have a significant global impact. Pressurized metered dose inhalers (pMDIs) are widely used for treatment, but they can have limitations such as high medication release speed resulting in drug deposition in the mouth or oral cavity and difficulty achieving proper synchronization with inhalation by users. Spacers are add-on devices that improve the efficiency of pMDIs by reducing the release speed and providing space for aerosol particle breakup to have finer and medically effective medication. The aim of this study is to optimize the size and cylindrical shape of spacers to enhance their drug delivery performance. The study was based on fluid dynamics theory and employed Ansys software for simulation and optimization. Results showed that optimization of the spacer's geometry greatly influenced its performance and improved drug delivery. This study provides a foundation for future research on enhancing the efficiency of inhalation therapy for lung diseases.

Keywords: asthma, COPD, pressurized metered dose inhalers, spacers, CFD, shape optimization

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Pei Chi Fang, Wei Chen Lin

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Trichomonas tenax is a microaerophilic oral protozoan found in patients with poor oral hygiene. It participates in the inflammatory process of periodontal disease and can potentially be aspirated into the lungs, giving rise to pulmonary trichomoniasis. However, the precise roles of T. tenax in the pulmonary system remain largely unexplored and warrant comprehensive epidemiological investigation. To assess the prevalence of T. tenax infection, we collected bronchoalveolar lavage fluid (BALF) samples from hospitalized patients with lung diseases. A specific nested PCR approach was employed to determine prevalence rates, yielding 21 positive cases out of 61 samples from Ditmanson Medical Foundation Chia-Yi Christian Hospital, and 11 positive cases out of 55 samples from National Cheng Kung University Hospital. Furthermore, there is a critical need for comprehensive data regarding the presence of T. tenax in environmental surface watersheds. In this context, we present findings from investigations in the Yanshuei and Donggang river basins in southern Taiwan, which are crucial sources for public drinking water in the region. In order to elucidate potential implications on pulmonary virus infections, we conducted an analysis of gene expression level changes in H292 cell line after exposure to T. tenax. Our findings revealed significant regulation of multiple virus-related genes, including IFI44L and IFITM3. Ongoing research endeavors are focused on identifying the key components within T. tenax responsible for these observed effects. Crucially, this study lays the groundwork for a preliminary understanding of T. tenax prevalence in patients with pulmonary diseases. It also seeks to establish a meaningful correlation between lung infections and oral hygiene practices, with the ultimate aim of informing distinct treatment and prevention strategies.

Keywords: parasitology, genes, virus, human health, infection, lung

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Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

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Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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Authors: Khaled M. Alqahtani

Abstract:

Copy number alterations (CNA) are variations in the structure of the genome, where certain regions deviate from the typical two chromosomal copies. These alterations are pivotal in understanding tumor progression and are indicative of patients' survival outcomes. However, effectively modeling patients' survival based on their genomic CNA profiles while identifying relevant genomic regions remains a statistical challenge. Various methods, such as the Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties, have been proposed but often overlook the inherent dependencies between genomic regions, leading to results that are hard to interpret. In this study, we enhance the elastic net penalty by incorporating an additional penalty that accounts for these dependencies. This approach yields smooth parameter estimates and facilitates variable selection, resulting in a sparse solution. Our findings demonstrate that this method outperforms other models in predicting survival outcomes, as evidenced by our simulation study. Moreover, it allows for a more meaningful interpretation of genomic regions associated with patients' survival. We demonstrate the efficacy of our approach using both real data from a lung cancer cohort and simulated datasets.

Keywords: copy number alterations, cox proportional hazard, lung cancer, regression, sparse solution

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Authors: Nicole Ramlachan, Samuel Mark West

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Lung cancer is the leading cause of cancer-associated deaths in North America, with the vast majority being non-small cell lung cancer (NSCLC), with a five-year survival rate of only 24%. Non-invasive discovery of biomarkers associated with early-diagnosis of NSCLC can enable precision oncology efforts using liquid biopsy-based multiomics profiling of plasma. Although tissue biopsies are currently the gold standard for tumor profiling, this method presents many limitations since these are invasive, risky, and sometimes hard to obtain as well as only giving a limited tumor profile. Blood-based tests provides a less-invasive, more robust approach to interrogate both tumor- and non-tumor-derived signals. We intend to examine 30 stage III-IV NSCLC patients pre-surgery and collect plasma samples.Cell-free DNA (cfDNA) will be extracted from plasma, and next-generation sequencing (NGS) performed. Through the analysis of tumor-specific alterations, including single nucleotide variants (SNVs), insertions, deletions, copy number variations (CNVs), and methylation alterations, we intend to identify tumor-derived DNA—ctDNA among the total pool of cfDNA. This would generate data to be used as an accurate form of cancer genotyping for diagnostic purposes. Using liquid biopsies offer opportunities to improve the surveillance of cancer patients during treatment and would supplement current diagnosis and tumor profiling strategies previously not readily available in Trinidad and Tobago. It would be useful and advantageous to use this in diagnosis and tumour profiling as well as to monitor cancer patients, providing early information regarding disease evolution and treatment efficacy, and reorient treatment strategies in, timethereby improving clinical oncology outcomes.

Keywords: genomics, multiomics, clinical genetics, genotyping, oncology, diagnostics

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Authors: Onmanee Prajuabjinda, Pakakrong Thondeeying, Jipisute Chunthorng-Orn, Bhanuz Dechayont, Arunporn Itharat

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A Thai medicinal preparation has been used for cancer treatment more than ten years ago in Khampramong Temple. Tectona grandis stem is one ingredient of this Thai medicinal remedy. The ethanolic extract of Tectona grandis stem showed the highest cytotoxic activities against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23) (IC50 = 3.92 and 7.78 µg/ml, respectively). It was isolated by bioassay-guided isolation method. Tectoquinone, a anthraquinone compound was isolated from this plant. This compound showed high specific cytotoxicity against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23)(IC50 =16.15 and 47.56 µg/ml or 72.67 and 214.00 µM, respectively). However, it showed less cytotoxic activity than the crude extract. In conclusion, tectoquinone as a main compound, is not the best cytotoxic compound from Tectona grandis, so there are more active cytotoxic compounds in this extract which should be isolated in the future. Moreover, tectoquinone displayed specific cytotoxicity against only human breast adenocarcinoma (MCF-7) which is a good criterion for cancer treatment.

Keywords: Tectona grandis, SRB assay, cytotoxicity, tectoquinone

Procedia PDF Downloads 409