Search results for: multi-abdominal organ segmentation

Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Saurabh Farkya, Govinda Surampudi

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Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

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Authors: A. Lubis, R. Widayanti, Z. Hikmah, A. Endaryanto, A. Harsono, A. Harianto, R. Etika, D. K. Handayani, M. Sampurna

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Neonatal lupus erythematous (NLE) is a rare disease marked by clinical characteristic and specific maternal autoantibody. Many cutaneous, cardiac, liver, and hematological manifestations could happen with affect of one organ or multiple. In this case, both babies were premature, low birth weight (LBW), small for gestational age (SGA) and born through caesarean section from a systemic lupus erythematous (SLE) mother. In the first case, we found a baby girl with dyspnea and grunting. Chest X ray showed respiratory distress syndrome (RDS) great I and echocardiography showed small atrial septal defect (ASD) and ventricular septal defect (VSD). She also developed anemia, thrombocytopenia, elevated C-reactive protein, hypoalbuminemia, increasing coagulation factors, hyperbilirubinemia, and positive blood culture of Klebsiella pneumonia. Anti-Ro/SSA and Anti-nRNP/sm were positive. Intravenous fluid, antibiotic, transfusion of blood, thrombocyte concentrate, and fresh frozen plasma were given. The second baby, male presented with necrotic tissue on the left ear and skin rashes, erythematous macula, athropic scarring, hyperpigmentation on all of his body with various size and facial haemorrhage. He also suffered from thrombocytopenia, mild elevated transaminase enzyme, hyperbilirubinemia, anti-Ro/SSA was positive. Intravenous fluid, methyprednisolone, intravenous immunoglobulin (IVIG), blood, and thrombocyte concentrate transfution were given. Two cases of neonatal lupus erythematous had been presented. Diagnosis based on clinical presentation and maternal auto antibody on neonate. Organ involvement in NLE can occur as single or multiple manifestations.

Keywords: neonatus lupus erythematous, maternal autoantibody, clinical characteristic, multiple organ manifestation

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Mihika Shivkumar, Krishna Kumar, C. Perisamy

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3D printing is a method of manufacturing wherein materials, such as plastic or metal, are deposited in layers one on top of the other to produce a three dimensional object. 3D printing is most commonly associated with creating engineering prototypes. However, its applications in the field of human health care have been frequently disregarded. Medical applications for 3D printing are expanding rapidly and are envisaged to revolutionize health care. Medical applications for 3D printing, both present and its potential, can be categorized broadly, including: creation of customized prosthetics tissue and organ fabrication; creation of implants, and anatomical models and pharmaceutical research regarding drug dosage forms. This piece breaks down bioprinting in the healthcare sector. It focuses on the better subtle elements of every particular point, including how 3D printing functions in the present, its impediments, and future applications in the health care sector.

Keywords: bio-printing, prototype, drug delivery, organ regeneration

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Authors: Keyur Joshi, Philip Dietrich, Tjark Windisch, Markus König

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In the field of surveillance-based fire detection, the volume of incoming data is increasing rapidly. However, the labeling of a large industrial dataset is costly due to the high annotation costs associated with current state-of-the-art methods, which often require bounding boxes or segmentation masks for model training. This paper introduces VideoAssist, a video annotation solution that utilizes a video-based foundation model to annotate entire videos with minimal effort, requiring the labeling of bounding boxes for only a few keyframes. To the best of our knowledge, VideoAssist is the first method to significantly reduce the effort required for labeling fire detection videos. The approach offers bounding box and segmentation annotations for the video dataset with minimal manual effort. Results demonstrate that the performance of labels annotated by VideoAssist is comparable to those annotated by humans, indicating the potential applicability of this approach in fire detection scenarios.

Keywords: fire detection, label annotation, foundation models, object detection, segmentation

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Ahmed Elmarhomy, K. Terada

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An automated method for counting passerby has been proposed using virtual-vertical measurement lines. Space-time image is representing the human regions which are treated using the segmentation process. Different color space has been used to perform the template matching. A proper template matching has been achieved to determine direction and speed of passing people. Distinguish one or two passersby has been investigated using a correlation between passerby speed and the human-pixel area. Finally, the effectiveness of the presented method has been experimentally verified.

Keywords: counting people, measurement line, space-time image, segmentation, template matching

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Sourav Ghosh, Antony Gomes

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Since 1894 anti-snake venom serum (ASVS) is the only available treatment against snake envenomation, although there are many side effects and limitations. The need for a supportive treatment was felt for a long time to overcome the side effects and limitations of ASVS. Andrographolide conjugated with gold nanoparticle (A-GNP) has been found to antagonize viper venom-induced local damages. The present study was aimed to study the protective efficacy of A-GNP against Viper venom-induced inflammatory response and organ toxicity in animal model. Ethical clearance was obtained from animal experiments. Physico-chemical characterization of A-GNP was done by DLS (diameter and zeta potential), FE-SEM and XRD. Swiss albino male mice were divided into 4 groups: Gr.1-Sham control, Gr.2- Russell’s Viper venom (RVV) control, Gr.3- andrographolide treated and Gr.4- A-GNP treated. The 1/5th minimum lethal dose of RVV (500µg/kg, s.c.) was induced in animals of group 2, 3 & 4 animals, followed by treatment with andrographolide (100mg/kg, i.p.) and A-GNP (100mg/kg, i.v.) in group 3 & 4 animals, respectively. Blood was collected after 18 h, serum was prepared, and inflammatory markers (IL 1β, 6, 17a, 10, TNF α) and biochemical markers (AST, ACP, LDH, urea, creatinine) were assessed. Values were expressed as mean±SEM (n=4), one way ANOVA was done, P<0.05 was considered as statistically significant. DLS size showed the hydrodynamic diameter of A-GNP to be 230-260nm with polydispersity index of 0.103 and zeta potential was -18.32mV. XRD data confirmed the presence of crystalline gold in A-GNP, and FESEM indicated the presence of nearly spherical particle with size18-24nm.Treatment with A-GNP significantly decreased viper venom-induced proinflammatory markers (IL 1β, 6, 17, TNF α) increased anti-inflammatory markers (IL 10) and decreased organ toxicity markers (AST, ACP, LDH, urea, creatinine) in animal model. Venom neutralization efficacy of A-GNP was > andrographolide, which confirmed the increased efficacy of andrographolide after gold nanoparticle conjugation. Venom neutralization by A-GNP was due to anti-oxidant/anti-inflammatory activity of andrographolide, which showed increased efficacy after gold nanoparticle tagging. Thus, A-GNP may serve as a supportive therapy in snake-bite (against inflammatory response and organ toxicity) subject to further detail studies.

Keywords: andrographolide, gold nanoparticle, inflammatory response, organ toxicity, snake venom, snake venom neutralization, viper venom

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Authors: Prabhvir Singh Marway, Kai Lok Chan, Maria-Ruxandra Jinga, Rachel Bok Ying Lee, Matthew Bok Kit Lee, Krishan Nandapalan, Sze Yi Beh, Harry Carr, Christopher Kui

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We piloted a structured series of online workshops on the 3D segmentation of anatomical structures from CT scans. 33 participants were recruited from four UK universities for two-day workshops between 2020 and 2021. Open-source software (3D-Slicer) was used. We hypothesized that active participation via real-time screen-sharing and voice-communication via Discord would enable improved engagement and learning, despite national lockdowns. Written feedback indicated positive learning experiences, with subjective measures of anatomical understanding and software confidence improving.

Keywords: medical education, workshop, segmentation, anatomy

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Authors: Mehdi Nematimoez

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Head posture is paramount to retaining gaze and balance in many activities; its control is thus important in many activities. However, little information is available about the effects of head movement restriction on other spine segment kinematics and movement patterns during lifting and lowering tasks. The aim of this study was to examine the effects of head movement restriction on relative angles and their derivatives using the stepwise segmentation approach during lifting and lowering tasks. Ten healthy men lifted and lowered a box using two styles (stoop and squat), with two loads (i.e., 10 and 20% of body weight); they performed these tasks with two instructed head postures (1. Flexing the neck to keep contact between chin and chest over the task cycle; 2. No instruction, free head posture). The spine was divided into five segments, tracked by six cluster markers (C7, T3, T6, T9, T12, and L5). Relative angles between spine segments and their derivatives (first and second) were analyzed by a stepwise segmentation approach to consider the effect of each segment on the whole spine. Accordingly, head posture significantly affected the derivatives of the relative angles and manifested latency in spine segments movement, i.e., cephalad-to-caudad or caudad-to-cephalad patterns. The relative angles for C7-T3 and T3-T6 increased over the cycle of all lifting and lowering tasks; nevertheless, in lower segments increased significantly when the spine moved into upright standing. However, these effects were clearer during lifting than lowering. Conclusively, the neck flexion can unevenly increase the flexion angles of spine segments from cervical to lumbar over lifting and lowering tasks; furthermore, stepwise segmentation reveals potential for assessing the segmental contribution in spine ROM and movement patterns.

Keywords: head movement restriction, spine kinematics, lifting, lowering, stepwise segmentation

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Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Alexander V. Spirov, David M. Holloway, Ekaterina M. Myasnikova

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Segmentation of the early Drosophila embryo results from the dynamic establishment of spatial gene expression patterns. Patterning occurs on an embryo geometry which is a 'deformed' prolate ellipsoid, with anteroposterior and dorsal-ventral major and minor axes, respectively. Patterning is largely independent along each axis, but some interaction can be seen in the 'bending' of the segmental expression stripes. This interaction is not well understood. In this report, we investigate how 3D geometrical features of the early embryo affect the segmental expression patterning. Specifically, we study the effect of geometry on formation of the Bicoid primary morphogenetic gradient. Our computational results demonstrate that embryos with a much longer ventral than dorsal surface ('bellied') can produce curved Bicoid concentration contours which could activate curved stripes in the downstream pair-rule segmentation genes. In addition, we show that having an extended source for Bicoid in the anterior of the embryo may be necessary for producing the observed exponential form of the Bicoid gradient along the anteroposterior axis.

Keywords: Drosophila embryo, bicoid morphogenetic gradient, exponential expression profile, expression surface form, segmentation genes, 3D modelling

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Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Kuplevatsky V., Kuplevatskay, Cherkashin M., Berezina N.

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After 6 months, a violation of the differentiation of the structure of the gland due to edema in 100%. 20% retained signs of a tumor according to DWI/ADC data. By 12 months, the reduction in the size of the gland is 100%. In all cases, no diffusion restriction was observed. The study after 18 months showed no significant changes in all (100%) patients. In the study, 24 months after treatment, the size of the gland was stable in all cases (+/- up to 5%). Diffuse decrease in T2VI signals from peripheral zones, without signs of diffusion restriction in 100%. After 30 months, signs of recovery of adenomatous changes in the transient zone were revealed in 85%. After 36 and 42 months, the restoration of organ differentiation was observed in 93% of patients. In 4 patients, by the 48th month, signs of biochemical relapse were clinically noted. According to the MRI data, signs of a local relapse were revealed. After 48 months, there were signs of restoration of organ differentiation, which allowed the use of PI-RADS criteria. The study after 54 months showed no changes compared to the control. 60 months after treatment, 97% of patients showed a restoration of differentiation of the gland structure, which allows evaluating the organ according to PI-RADS criteria Conclusions: The beginning of restoration of the structure of the prostate gland began 24 months after proton radiation therapy, the PI-RADS criteria can be fully applied after 48 months of treatment. Control studies every 6 months without clinical signs of relapse are not advisable. Local control of the prostate tumor after proton radiation therapy was achieved in 95% of patients during the entire follow-up period ( 60 months).

Keywords: proton therapy, prostate cancer, MRI imaging, PI-RADS

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Authors: Fatima Mokeddem

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The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

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Authors: Noor Hasmini Abdghani, Nik Kamariah Nikmat, Nor Hayati Ahmad

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Rapid growth of the internet technology led to changes in the consumer lifestyles. This involved customer buying behaviour-based internet that create new kind of buying strategy. Hence, it has summoned many of world firms including Malaysia to generate new quality strategy in preparation to face new customer buying lifestyles. Particularly, this study focused on identifying online customer segment of automobile passenger car customers. Secondly, the objective is to understand online customer’s receptiveness towards internet technologies. This study distributed 700 questionnaires whereby 582 were returned representing 83% response rate. The data were analysed using factor and regression analyses. The result from the factor analysis precipitates four online passenger car segmentations in Malaysia, which are: Segment (1)- Automobile Online shopping Preferences, Segment (2)- Automobile Online Brand Comparison, Segment (3)- Automobile Online Information Seeking and Segment (4)- Automobile Offline Shopping Preferences. In understanding the online customer’s receptiveness towards internet, the regression result shows that there is significant relationship between each of four segments of online passenger car customer with attitude towards automobile online shopping. This implies that, for online customers to have receptiveness toward internet technologies, he or she must have preferences toward online shopping or at least prefer to browse any related information online even if the actual purchase is made at the traditional store. With this proposed segmentation strategy, the firms especially the automobile firms will be able to understand their online customer behavior. At least, the proposed segmentation strategy will help the firms to strategize quality management approach for their online customers’ buying decision making.

Keywords: Automobile, Market Segmentation, Online Shopping Attitude, Quality Management Strategy

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Authors: Mohamed Mamdouh Al-Banna, Warda Youssef Mohamed Morsy, Hanaa Ali El-Feky, Ashraf Hussein Abdelmohsen

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Background: The mechanically ventilated patients need a special nursing care with continuous closed observation. The patients’ body mass index may affect their prognosis or outcomes. Aim of the study: to investigate the relationship between BMI and selected outcomes of critically ill mechanically ventilated patients. Research Design: A descriptive correlational research design was utilized Research questions: a) what is the BMI profile of mechanically ventilated patients admitted to critical care units over a period of six months? b) What is the relationship between body mass index and frequency of organ dysfunction, length of ICU stay, weaning from mechanical ventilation, and the mortality rate among adult critically ill mechanically ventilated patients? Setting: different intensive care units of Cairo University Hospitals. Sample: A convenience sample of 30 mechanically ventilated patients for at least 72 hours. Tools of data collection: Three tools were utilized to collect data pertinent to the current study: tool 1: patients’ sociodemographic and medical data sheet, tool 2: BURNS Wean Assessment Program (BWAP) checklist, tool 3: Sequential organ failure assessment (SOFA score) sheet. Results: The majority of the studied sample (77%) was males, and (26.7 %) of the studied sample were in the age group of 18-28 years old, and (26.7 %) were in the age group of 40-50 years old. Moreover, two thirds (66.7%) of the studied sample were within normal BMI. No significant statistical relationship between BMI category and ICU length of stay or the mortality rate among the studied sample, (X² = 11.31, P value = 0.79), (X² = 0.15, P value = 0.928) respectively. No significant statistical relationship between BMI category and the weaning trials from mechanical ventilation among the studied sample, (X² = 0.15, P value = 0.928). No significant statistical relationship was found between BMI category and the occurrence of organ dysfunction among the studied sample, (X² = 2.54, P value = 0.637). Conclusion: No relationship between the BMI categories and the selected patients’ outcomes (weaning from MV, length of ICU stay, occurrence of organ dysfunction, mortality rate). Recommendations: Replication of this study on a larger sample from different geographical locations in Arab Republic of Egypt, conducting farther studies to assess the effect of the quality of nursing care on the mechanically ventilated patients’ outcomes.

Keywords: mechanical ventilation, body mass index, outcomes of mechanically ventilated patient, organ failure

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Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

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Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of living tissues to mechanical loads is necessary for a wide range of developing fields such as prosthetics design or computerassisted surgical interventions. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically, growth is one of the main sources. Extracting body organ’s shapes from medical imaging does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is gravity since an organ grows under its influence from birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. This paper presents an original computational framework based on gradual growth to determine the residual stresses due to growth. To illustrate the method, we apply it to a finite element model of a healthy human face reconstructed from medical images. The distribution of residual stress in facial tissues is computed, which can overcome the effect of gravity and maintain tissues firmness. Our assumption is that tissue wrinkles caused by aging could be a consequence of decreasing residual stress and thus not counteracting gravity. Taking into account these stresses seems therefore extremely important in maxillofacial surgery. It would indeed help surgeons to estimate tissues changes after surgery.

Keywords: finite element method, growth, residual stress, soft tissue

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

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The study uses an image analysis technique employing thermal imaging to measure the percentage of areas with various temperatures on a freezing surface. An image segmentation method using threshold values is applied to a sequence of image recording the freezing process. The phenomenon is transient and temperatures vary fast to reach the freezing point and complete the freezing process. Freezing salt water is subjected to the salt rejection that makes the freezing point dynamic and dependent on the salinity at the phase interface. For a specific area of freezing, nucleation starts from one side and end to another side, which causes a dynamic and transient temperature in that area. Thermal cameras are able to reveal a difference in temperature due to their sensitivity to infrared radiance. Using Experimental setup, a video is recorded by a thermal camera to monitor radiance and temperatures during the freezing process. Image processing techniques are applied to all frames to detect and classify temperatures on the surface. Image processing segmentation method is used to find contours with same temperatures on the icing surface. Each segment is obtained using the temperature range appeared in the image and correspond pixel values in the image. Using the contours extracted from image and camera parameters, stratified areas with different temperatures are calculated. To observe temperature contours on the icing surface using the thermal camera, the salt water sample is dropped on a cold surface with the temperature of -20°C. A thermal video is recorded for 2 minutes to observe the temperature field. Examining the results obtained by the method and the experimental observations verifies the accuracy and applicability of the method.

Keywords: ice contour boundary, image processing, image segmentation, salt ice, thermal image

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Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

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Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

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Authors: Kabil Boukhari

Abstract:

In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

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Authors: Marwan Jarrah, Nadia Nugrush, Sukainah Ali, Areej Allawzi

Abstract:

This research article investigates how illnesses (different types and severity) are expressed in Arabic discourse with a particular focus on input coming from Colloquial Jordanian Arabic (CJA). Drawing on a corpus of naturally occurring conversations, this article offers evidence that illnesses are predominantly expressed through two different sets of expressive strategies, namely direct expressive strategies (DES) and indirect expressive strategies (IES). The latter are exclusively used when cancer and mental health disorders are targeted. IES include the substitution of the name of the illness with some religious expressions (e.g., ʔallah ʔijdʒi:rna ‘May Allah keeps us safe’) or certain terms especially when cancer is meant (e.g., haðˤa:k ʔil-maraðˤ ‘that disease’). On the other hand, DES are used in conjunction with other illnesses (e.g., heart, kidneys, diabetes, etc.), regardless of their severity. DES include specific formulas that remarkably mention the name of the inflicted organ (e.g., [with-SOMEONE the ORGAN] as in ʕinduh ʔil-qalb ‘lit. with-him the heart’ meaning ‘He has a heart disease). We discuss the effects of religious beliefs and local norms and values in determining the use of these strategies.

Keywords: Illnesses, pragmatics, expressive strategies, religion

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Authors: Wilai Masanga, Chirapha Tannanonta, Sangutid Thongsawad, Sasikarn Chamchod, Todsaporn Fuangrod

Abstract:

The major factors of radiotherapy for head and neck (HN) cancers include patient’s anatomical changes and tumour shrinkage. These changes can significantly affect the planned dose distribution that causes the treatment plan deterioration. A measured transit EPID images compared to a predicted EPID images using gamma analysis has been clinically implemented to verify the dose accuracy as part of adaptive radiotherapy protocol. However, a global gamma analysis dose not sensitive to some critical organ changes as the entire treatment field is compared. The objective of this feasibility study is to evaluate the dosimetric response to patient anatomical changes during the treatment course in HN IMRT (Head and Neck Intensity-Modulated Radiation Therapy) using a novel comparison method; organ-of-interest gamma analysis. This method provides more sensitive to specific organ change detection. Random replanned 5 HN IMRT patients with causes of tumour shrinkage and patient weight loss that critically affect to the parotid size changes were selected and evaluated its transit dosimetry. A comprehensive physics-based model was used to generate a series of predicted transit EPID images for each gantry angle from original computed tomography (CT) and replan CT datasets. The patient structures; including left and right parotid, spinal cord, and planning target volume (PTV56) were projected to EPID level. The agreement between the transit images generated from original CT and replanned CT was quantified using gamma analysis with 3%, 3mm criteria. Moreover, only gamma pass-rate is calculated within each projected structure. The gamma pass-rate in right parotid and PTV56 between predicted transit of original CT and replan CT were 42.8%( ± 17.2%) and 54.7%( ± 21.5%). The gamma pass-rate for other projected organs were greater than 80%. Additionally, the results of organ-of-interest gamma analysis were compared with 3-dimensional cone-beam computed tomography (3D-CBCT) and the rational of replan by radiation oncologists. It showed that using only registration of 3D-CBCT to original CT does not provide the dosimetric impact of anatomical changes. Using transit EPID images with organ-of-interest gamma analysis can provide additional information for treatment plan suitability assessment.

Keywords: re-plan, anatomical change, transit electronic portal imaging device, EPID, head, and neck

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Authors: R. M. Korzerzer, J. O. Hambolu, S. O. Salami, S. B. Oladele

Abstract:

Twelve apparently healthy grasscutters between the ages of three and seven months were used for this study. The animals were purchased from local breeders in Oturkpo, Benue state, Nigeria and transported to the research laboratory in the Department of Veterinary Anatomy, Ahmadu Bello University, Zaria by means of constructed cages. The animals were divided into three groups according to their ages and acclimatised. Sacrifice was done using chloroform gaseous inhalation anaesthesia. An incision was made at the neck region and the thymus located and identified by its prominent bilateral nature. Extirpated thymuses from each animal were immediately weighed and fixed in Bouin’s fluid for 48 hours. The tissues were then prepared using standard methods. Haematoxilin and eosin was used for routine histology and Rhodamine B aniline methylene blue was for studying the architecture of the elastic and reticular fibres of the thymus. Grossly, the thymus appeared as a bilateral organ on either side of the thoracic midline. The organ size decreased consistently as the animals advanced in age. Mean ± SEM values for thymic weights were 1.23 ± 0.048 g, 0.53 ± 0.019 g and 0.30 ± 0.042 g at three, five and seven months of age respectively.

Keywords: gross, histological, thymus, grasscutter

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