Search results for: nerve segmentation
401 Object Detection Based on Plane Segmentation and Features Matching for a Service Robot
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
Procedia PDF Downloads 547400 Image Segmentation: New Methods
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
Procedia PDF Downloads 276399 Improvement of Sleep Quality Through Manual and Non-Pharmacological Treatment
Authors: Andreas Aceranti, Sergio Romanò, Simonetta Vernocchi, Silvia Arnaboldi, Emilio Mazza
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As a result of the Sars-Cov2 pandemic, the incidence of thymism disorders has significantly increased and, often, patients are reluctant to want to take drugs aimed at stabilizing mood. In order to provide an alternative approach to drug therapies, we have prepared a study in order to evaluate the possibility of improving the quality of life of these subjects through osteopathic treatment. Patients were divided into visceral and fascial manual treatment with the aim of increasing serotonin levels and stimulating the vagus nerve through validated techniques. The results were evaluated through the administration of targeted questionnaires in order to assess quality of life, mood, sleep and intestinal functioning. At a first endpoint we found, in patients undergoing fascial treatment, an increase in quality of life and sleep: in fact, they report a decrease in the number of nocturnal awakenings; a reduction in falling asleep times and greater rest upon waking. In contrast, patients undergoing visceral treatment, as well as those included in the control group, did not show significant improvements. Patients in the fascial group have, in fact, reported an improvement in thymism and subjective quality of life with a generalized improvement in function. Although the study is still ongoing, based on the results of the first endpoint we can hypothesize that fascial stimulation of the vagus nerve with manual and osteopathic techniques may be a valid alternative to pharmacological treatments in mood and sleep disorders.Keywords: ostheopathy, insomnia, noctural awakening, thymism
Procedia PDF Downloads 90398 Comparison of Central Light Reflex Width-to-Retinal Vessel Diameter Ratio between Glaucoma and Normal Eyes by Using Edge Detection Technique
Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong
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Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.Keywords: glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection
Procedia PDF Downloads 325397 The Implementation of the Javanese Lettered-Manuscript Image Preprocessing Stage Model on the Batak Lettered-Manuscript Image
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
Procedia PDF Downloads 401396 Optical Imaging Based Detection of Solder Paste in Printed Circuit Board Jet-Printing Inspection
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
Procedia PDF Downloads 336395 Hyperspectral Image Classification Using Tree Search Algorithm
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
Procedia PDF Downloads 178394 Antioxidant Effects of C-Phycocyanin on Oxidized Astrocyte in Brain Injury Using 2D and 3D Neural Nanofiber Tissue Model
Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin
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In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect
Procedia PDF Downloads 321393 Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier
Authors: Abdulkader Helwan
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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
Procedia PDF Downloads 534392 Seashore Debris Detection System Using Deep Learning and Histogram of Gradients-Extractor Based Instance Segmentation Model
Authors: Anshika Kankane, Dongshik Kang
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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
Procedia PDF Downloads 107391 Microbioreactor System for Cell Behavior Analysis Focused on Nerve Tissue Engineering
Authors: Yusser Olguín, Diego Benavente, Fernando Dorta, Nicole Orellana, Cristian Acevedo
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One of the greatest challenges of tissue engineering is the generation of materials in which the highest possible number of conditions can be incorporated to stimulate the proliferation and differentiation of cells, which will be transformed together with the material into new functional tissue. In this sense, considering the properties of microfluidics and its relationship with cellular micro-environments, the possibility of controlling flow patterns and the ability to design diverse patterns in the chips, a microfluidic cell culture system can be established as a means for the evaluation of the effect of different parameters in a controlled and precise manner. Specifically in relation to the study and development of alternatives in peripheral nervous tissue engineering, it is necessary to consider different physical and chemical neurotrophic stimuli that promote cell growth and differentiation. Chemical stimuli include certain vitamins, glucocorticoids, gangliosides, and growth factors, while physical stimuli include topological stimuli, mechanical forces of the cellular environment and electrical stimulation. In this context, the present investigation shows the results of cell stimulation in a microbioreactor using electrical and chemical stimuli, where the differentiation of PC12 cells as a neuronal model is evidenced by neurite expression, dependent on the stimuli and their combination. The results were analysed with a multi-factor statistical approach, showing several relationships and dependencies between different parameters. Chip design, operating parameters and concentrations of neurotrophic chemical factors were found to be preponderant, based on the characteristics of the electrical stimuli.Keywords: microfluidics, nerve tissue engineering, microbioreactor, electrical stimuli
Procedia PDF Downloads 86390 Automated Ultrasound Carotid Artery Image Segmentation Using Curvelet Threshold Decomposition
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
Procedia PDF Downloads 342389 Content Based Video Retrieval System Using Principal Object Analysis
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
Procedia PDF Downloads 302388 Autonomic Nervous System Changes Associated with Rheumatoid Arthritis: Clinical and Electrophysiological Study
Authors: Emmanuel Kamal Aziz Saba, Hussein Al-Moghazy Sultan
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The aim of this study was to evaluate clinically and electro physiologically the autonomic nervous system changes associated with rheumatoid arthritis (RA). The present study included 25 patients with RA [22 women (88%)] and 30 apparently healthy control subjects [27 women (90%)]. A thorough clinical examination was carried out. Disease activity and functional disability were assessed. Tests for assessment of autonomic functions include active and passive orthostatic stress tests, and sympathetic skin response (SSR). The presence of abnormality in 2 tests or more was a clue for the presence of autonomic neuropathy (AN). Sural sensory nerve conduction study and posterior tibial motor nerve conduction study were done. There was a statistically significant decrease in standing systolic and diastolic blood pressure (BP) components of the active orthostatic stress test and SSR amplitude as well as statistically significant prolongation of SSR latency of RA patients when compared to control. Three patients (12%) had clinical symptoms suggestive of AN; increased to 14 patients (56 %) when orthostatic stress tests and SSR were utilized. There were no statistically significant differences between patients with different disease activity score 28 with 4 variables grades of RA activity and SSR latency and amplitude. There were no statistically significant differences between patients with different Stanford Health Assessment Questionnaire Disability Index grades of RA functional disability and SSR latency and amplitude. In conclusion, autonomic neuropathy is a common extra-articular manifestation of RA affecting sympathetic and parasympathetic fibers.Keywords: autonomic neuropathy, orthostatic stress test, rheumatoid arthritis, sympathetic skin response
Procedia PDF Downloads 360387 Robustness Conditions for the Establishment of Stationary Patterns of Drosophila Segmentation Gene Expression
Authors: Ekaterina M. Myasnikova, Andrey A. Makashov, Alexander V. Spirov
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First manifestation of a segmentation pattern in the early Drosophila development is the formation of expression domains (along with the main embryo axis) of genes belonging to the trunk gene class. Highly variable expression of genes from gap family in early Drosophila embryo is strongly reduced by the start of gastrulation due to the gene cross-regulation. The dynamics of gene expression is described by a gene circuit model for a system of four gap genes. It is shown that for the formation of a steep and stationary border by the model it is necessary that there existed a nucleus (modeling point) in which the gene expression level is constant in time and hence is described by a stationary equation. All the rest genes expressed in this nucleus are in a dynamic equilibrium. The mechanism of border formation associated with the existence of a stationary nucleus is also confirmed by the experiment. An important advantage of this approach is that properties of the system in a stationary nucleus are described by algebraic equations and can be easily handled analytically. Thus we explicitly characterize the cross-regulation properties necessary for the robustness and formulate the conditions providing this effect through the properties of the initial input data. It is shown that our formally derived conditions are satisfied for the previously published model solutions.Keywords: drosophila, gap genes, reaction-diffusion model, robustness
Procedia PDF Downloads 367386 Application of the Quantile Regression Approach to the Heterogeneity of the Fine Wine Prices
Authors: Charles-Olivier Amédée-Manesme, Benoit Faye, Eric Le Fur
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In this paper, the heterogeneity of the Bordeaux Legends 50 wine market price segment is addressed. For this purpose, quantile regression is applied – with market segmentation based on wine bottle price quantile – and the hedonic price of wine attributes is computed for various price segments of the market. The approach is applied to a major privately held data set which consists of approximately 30,000 transactions over the 2003–2014 period. The findings suggest that the relative hedonic prices of several wine attributes differ significantly among deciles. In particular, the elasticity coefficient of the expert ratings shows strong variation among prices. If - as suggested in the literature - expert ratings have a positive influence on wine price on average, they have a clearly decreasing impact over the quantiles. Finally, the lower the wine price, the higher the potential for price appreciation over time. Other variables such as chateaux or vintage are also shown to vary across the distribution of wine prices. While enhancing our understanding of the complex market dynamics that underlie Bordeaux wines’ price, this research provides empirical evidence that the QR approach adequately captures heterogeneity among wine price ranges, which simultaneously applies to wine stock, vintage and auctions’ house.Keywords: hedonics, market segmentation, quantile regression, heterogeneity, wine economics
Procedia PDF Downloads 340385 Multi-scale Geographic Object-Based Image Analysis (GEOBIA) Approach to Segment a Very High Resolution Images for Extraction of New Degraded Zones. Application to The Region of Mécheria in The South-West of Algeria
Authors: Bensaid A., Mostephaoui T., Nedjai R.
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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.Keywords: land development, GIS, sand dunes, segmentation, remote sensing
Procedia PDF Downloads 109384 Neuroprotection against N-Methyl-D-Aspartate-Induced Optic Nerve and Retinal Degeneration Changes by Philanthotoxin-343 to Alleviate Visual Impairments Involve Reduced Nitrosative Stress
Authors: Izuddin Fahmy Abu, Mohamad Haiqal Nizar Mohamad, Muhammad Fattah Fazel, Renu Agarwal, Igor Iezhitsa, Nor Salmah Bakar, Henrik Franzyk, Ian Mellor
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Glaucoma is the global leading cause of irreversible blindness. Currently, the available treatment strategy only involves lowering intraocular pressure (IOP); however, the condition often progresses despite lowered or normal IOP in some patients. N-methyl-D-aspartate receptor (NMDAR) excitotoxicity often occurs in neurodegeneration-related glaucoma; thus it is a relevant target to develop a therapy based on neuroprotection approach. This study investigated the effects of Philanthotoxin-343 (PhTX-343), an NMDAR antagonist, on the neuroprotection of NMDA-induced glaucoma to alleviate visual impairments. Male Sprague-Dawley rats were equally divided: Groups 1 (control) and 2 (glaucoma) were intravitreally injected with phosphate buffer saline (PBS) and NMDA (160nM), respectively, while group 3 was pre-treated with PhTX-343 (160nM) 24 hours prior to NMDA injection. Seven days post-treatments, rats were subjected to visual behavior assessments and subsequently euthanized to harvest their retina and optic nerve tissues for histological analysis and determination of nitrosative stress level using 3-nitrotyrosine ELISA. Visual behavior assessments via open field, object, and color recognition tests demonstrated poor visual performance in glaucoma rats indicated by high exploratory behavior. PhTX-343 pre-treatment appeared to preserve visual abilities as all test results were significantly improved (p < 0.05). H&E staining of the retina showed a marked reduction of ganglion cell layer thickness in the glaucoma group; in contrast, PhTX-343 significantly increased the number by 1.28-folds (p < 0.05). PhTX-343 also increased the number of cell nuclei/100μm2 within inner retina by 1.82-folds compared to the glaucoma group (p < 0.05). Toluidine blue staining of optic nerve tissues showed that PhTX-343 reduced the degeneration changes compared to the glaucoma group which exhibited vacuolation overall sections. PhTX-343 also decreased retinal 3- nitrotyrosine concentration by 1.74-folds compared to the glaucoma group (p < 0.05). All results in PhTX-343 group were comparable to control (p > 0.05). We conclude that PhTX-343 protects against NMDA-induced changes and visual impairments in the rat model by reducing nitrosative stress levels.Keywords: excitotoxicity, glaucoma, nitrosative stress , NMDA receptor , N-methyl-D-aspartate , philanthotoxin, visual behaviour
Procedia PDF Downloads 137383 Pain Management in Burn Wounds with Dual Drug Loaded Double Layered Nano-Fiber Based Dressing
Authors: Sharjeel Abid, Tanveer Hussain, Ahsan Nazir, Abdul Zahir, Nabyl Khenoussi
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Localized application of drug has various advantages and fewer side effects as compared with other methods. Burn patients suffer from swear pain and the major aspects that are considered for burn victims include pain and infection management. Nano-fibers (NFs) loaded with drug, applied on local wound area, can solve these problems. Therefore, this study dealt with the fabrication of drug loaded NFs for better pain management. Two layers of NFs were fabricated with different drugs. Contact layer was loaded with Gabapentin (a nerve painkiller) and the second layer with acetaminophen. The fabricated dressing was characterized using scanning electron microscope, Fourier Transform Infrared Spectroscopy, X-Ray Diffraction and UV-Vis Spectroscopy. The double layered based NFs dressing was designed to have both initial burst release followed by slow release to cope with pain for two days. The fabricated nanofibers showed diameter < 300 nm. The liquid absorption capacity of the NFs was also checked to deal with the exudate. The fabricated double layered dressing with dual drug loading and release showed promising results that could be used for dealing pain in burn victims. It was observed that by the addition of drug, the size of nanofibers was reduced, on the other hand, the crystallinity %age was increased, and liquid absorption decreased. The combination of fast nerve pain killer release followed by slow release of non-steroidal anti-inflammatory drug could be a good tool to reduce pain in a more secure manner with fewer side effects.Keywords: pain management, burn wounds, nano-fibers, controlled drug release
Procedia PDF Downloads 253382 Anesthesia for Spinal Stabilization Using Neuromuscular Blocking Agents in Dog: Case Report
Authors: Agata Migdalska, Joanna Berczynska, Ewa Bieniek, Jacek Sterna
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Muscle relaxation is considered important during general anesthesia for spine stabilization. In a presented case peripherally acting muscle relaxant was applied during general anesthesia for spine stabilization surgery. The patient was a dog, 11-years old, 26 kg, male, mix breed. Spine fracture was situated between Th13-L1-L2, probably due to the car accident. Preanesthetic physical examination revealed no sign underlying health issues. The dog was premedicated with midazolam 0.2 mg IM and butorphanol 2.4 mg IM. General anesthesia was induced with propofol IV. After the induction, the dog was intubated with an endotracheal tube and connected to an open-ended rebreathing system and maintained with the use of inhalation anesthesia with isoflurane in oxygen. 0,5 mg/ kg of rocuronium was given IV. Use of muscle relaxant was accompanied by an assessment of the degree of neuromuscular blockade by peripheral nerve stimulator. Electrodes were attached to the skin overlying at the peroneal nerve at the lateral cranial tibia. Four electrical pulses were applied to the nerve over a 2 second period. When satisfying nerve block was detected dog was prepared for the surgery. No further monitoring of the effectiveness of blockade was performed during surgery. Mechanical ventilation was kept during anesthesia. During surgery dog maintain stable, and no anesthesiological complication occur. Intraoperatively surgeon claimed that neuromuscular blockade results in a better approach to the spine and easier muscle manipulation which was helpful in order to see the fracture and replace bone fragments. Finally, euthanasia was performed intraoperatively as a result of vast myelomalacia process of the spinal cord. This prevented examination of the recovering process. Neuromuscular blocking agents act at the neuromuscular junction to provide profound muscle relaxation throughout the body. Muscle blocking agents are neither anesthetic nor analgesic; therefore inappropriately used may cause paralysis in fully conscious and feeling pain patient. They cause paralysis of all skeletal muscles, also diaphragm and intercostal muscles when given in higher doses. Intraoperative management includes maintaining stable physiological conditions, which involves adjusting hemodynamic parameters, ensuring proper ventilation, avoiding variations in temperature, maintain normal blood flow to promote proper oxygen exchange. Neuromuscular blocking agent can cause many side effects like residual paralysis, anaphylactic or anaphylactoid reactions, delayed recovery from anesthesia, histamine release, recurarization. Therefore reverse drug like neostigmine (with glikopyrolat) or edrofonium (with atropine) should be used in case of a life-threatening situation. Another useful drug is sugammadex, although the cost of this drug strongly limits its use. Muscle relaxant improves surgical conditions during spinal surgery, especially in heavily muscled individuals. They are also used to facilitate the replacement of dislocated joints as they improve conditions during fracture reduction. It is important to emphasize that in a patient with muscle weakness neuromuscular blocking agents may result in intraoperative and early postoperative cardiovascular and respiratory complications, as well as prolonged recovery from anesthesia. This should not appear in patients with recent spine fracture or luxation. Therefore it is believed that neuromuscular blockers could be useful during spine stabilization procedures.Keywords: anesthesia, dog, neuromuscular block, spine surgery
Procedia PDF Downloads 181381 Vagal Nerve Stimulator as a Treatment Approach in CHARGE Syndrome: A Case Report
Authors: Roya Vakili, Lekaa Elhajjmoussa, Barzin Omidi-Shal, Kim Blake
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Objective: The purpose of this case report is to highlight the successful treatment of a patient with Coloboma, Heart defect, Atresia choanae, Retarded growth and development, Genital hypoplasia, Ear anomalies/deafness, (CHARGE syndrome) using a vagal nerve stimulator (VNS). Background: This is the first documented case report, to the authors' best knowledge, for a patient with CHARGE syndrome, epilepsy, autism, and postural orthostatic tachycardia syndrome (POTS) that was successfully treated with an implanted VNS therapeutic device. Methodology: The study is a case report. Results: This is the case of a 24-year-old female patient with CHARGE syndrome (non-random association of anomalies Coloboma, Heart defect, Atresia choanae, Retarded growth and development, Genital hypoplasia, Ear anomalies/deafness) and several other comorbidities including refractory epilepsy, Patent Ductus Arteriosus (PDA) and POTS who had significant improvement of her symptoms after VNS implantation. She was a VNS candidate given her longstanding history of drug-resistant epilepsy and current disposition secondary to CHARGE syndrome. Prior to VNS implantation, she experienced three generalized seizures a year and daily POTS-related symptoms. She was having frequent lightheadedness and syncope spells due to a rapid heart rate and low blood pressure. The VNS device was set to detect a rapid heart rate and send appropriate stimulation anytime the heart rate exceeded 20% of the patient’s normal baseline. The VNS device demonstrated frequent elevated heart rates and concurrent VNS release every 8 minutes in addition to the programmed events. Following VNS installation, the patient became more active, alert, and communicative and was able to verbally communicate with words she was unable to say prior. Her GI symptoms also improved, as she was able to tolerate food better orally in addition to her G and J tube, likely another result of the vagal nerve stimulation. Additionally, the patient’s seizures and POTS-related cardiac events appeared to be well controlled. She had prolonged electroencephalogram (EEG) testing, showing no significant change in epileptiform activity. Improvements in the patient’s disposition are believed to be secondary to parasympathetic stimulation, adequate heart rate control, and GI stimulation, in addition to behavioral changes and other benefits via her implanted VNS. Conclusion: VNS showed promising results in improving the patient's quality of life and managing her diverse symptoms, including dysautonomia, POTs, gastrointestinal mobility, cognitive functioning as well seizure control.Keywords: autism, POTs, CHARGE, VNS
Procedia PDF Downloads 88380 Semiautomatic Calculation of Ejection Fraction Using Echocardiographic Image Processing
Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello
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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction
Procedia PDF Downloads 427379 Comparative Study Between Two Different Techniques for Postoperative Analgesia in Cesarean Section Delivery
Authors: Nermeen Elbeltagy, Sara Hassan, Tamer Hosny, Mostafa Abdelaziz
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Introduction: Adequate postoperative analgesia after caesarean section (CS) is crucial as it impacts the distinct surgical recovery needs of the parturient. Over recent years, there has been increased interest in regional nerve block techniques with promising results on efficacy. These techniques reduce the need for additional analgesia, thereby lowering the incidence of drug-related side effects. As postoperative pain after cesarean is mainly due to abdominal incision, the transverses abdomenis plane ( TAP ) block is a relatively new abdominal nerve block with excellent efficacy after different abdominal surgeries, including cesarean section. Objective: The main objective is to compare ultrasound-guided TAP block provided by the anesthesiologist with TAP provided by the surgeon through a caesarean incision regarding the duration of postoperative analgesia, intensity of analgesia, timing of mobilization, and easiness of the procedure. Method: Ninety pregnant females at term who were scheduled for delivery by elective cesarean section were randomly distributed into two groups. The first group (45) received spinal anesthesia and postoperative ultrasound guided TAP block using 20ml on each side of 0.25% bupivacaine which was provided by the anesthesiologist. The second group (45) received spinal anesthesia plus a TAP block using 20ml on each side of 0.25% bupivacaine, which was provided by the surgeon through the cesarean incision. Visual Analogue Scale (VAS) was used for the comparison between the two groups. Results: VAS score after four hours was higher among the TAP block group provided by the surgeon through the surgical incision than the postoperative analgesic profile using ultrasound-guided TAP block provided by the anesthesiologist (P=0.011). On the contrary, there was no statistical difference in the patient’s dose of analgesia after four hours of the TAP block (P=0.228). Conclusion: TAP block provided through the surgical incision is safe and enhances early patient’s mobilization.Keywords: TAP block, CS, VAS, analgesia
Procedia PDF Downloads 50378 3D-Printed Collagen/Chitosan Scaffolds Loaded with Exosomes Derived from Neural Stem Cells Pretreated with Insulin Growth Factor-1 for Neural Regeneration after Traumatic Brain Injury
Authors: Xiao-Yin Liu, Liang-Xue Zhou
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Traumatic brain injury (TBI), as a kind of nerve trauma caused by an external force, affects people all over the world and is a global public health problem. Although there are various clinical treatments for brain injury, including surgery, drug therapy, and rehabilitation therapy, the therapeutic effect is very limited. To improve the therapeutic effect of TBI, scaffolds combined with exosomes are a promising but challenging method for TBI repair. In this study, we examined whether a novel 3D-printed collagen/chitosan scaffold/exosomes derived from neural stem cells (NSCs) pretreated with insulin growth factor-1 (IGF-I) scaffolds (3D-CC-INExos) could be used to improve TBI repair and functional recovery after TBI. Our results showed that composite scaffolds of collagen-, chitosan- and exosomes derived from NSCs pretreated with IGF-I (INExos) could continuously release the exosomes for two weeks. In the rat TBI model, 3D-CC-INExos scaffold transplantation significantly improved motor and cognitive function after TBI, as assessed by the Morris water maze test and modified neurological severity scores. In addition, immunofluorescence staining and transmission electron microscopy showed that the recovery of damaged nerve tissue in the injured area was significantly improved by 3D-CC-INExos implantation. In conclusion, our data suggest that 3D-CC-INExos might provide a potential strategy for the treatment of TBI and lay a solid foundation for clinical translation.Keywords: traumatic brain injury, exosomes, insulin growth factor-1, neural stem cells, collagen, chitosan, 3D printing, neural regeneration, angiogenesis, functional recovery
Procedia PDF Downloads 82377 Particle Filter Supported with the Neural Network for Aircraft Tracking Based on Kernel and Active Contour
Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani
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In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.Keywords: video tracking, particle filter, greedy snake, neural network
Procedia PDF Downloads 343376 Computer-Aided Classification of Liver Lesions Using Contrasting Features Difference
Authors: Hussein Alahmer, Amr Ahmed
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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate. This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation
Procedia PDF Downloads 326375 A Fast Parallel and Distributed Type-2 Fuzzy Algorithm Based on Cooperative Mobile Agents Model for High Performance Image Processing
Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah
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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing
Procedia PDF Downloads 429374 Endoscopic Versus Open Treatment of Carpal Tunnel Syndrome: Postoperative Complications in Patients with Diabetes Mellitus
Authors: Arman Kishan, Mark Haft, Steve Li, Duc Nguyen, Dawn Laporte
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Objective: Patients with Type 2 diabetes (T2DM) often face higher postoperative complication rates. Limited data exist on outcomes in T2DM patients undergoing carpal tunnel release (CTR). This study aims to compare complication rates between endoscopic CTR (ECTR) and open CTR (OCTR) in patients with T2DM. Methods: This was a retrospective cohort study using the TriNetX database of 56741 patients with T2DM undergoing ECTR (N= 14,949) or OCTR (N= 41,792). Demographic data, medical comorbidities, and complication rates were analyzed. We used multivariable analysis to identify differences in postoperative complication rates between the two treatment methods in patients with T2DM. Results: Patients with T2DM undergoing ECTR had a significantly lower incidence of 90-day wound infection (p < 0.001), 90-day wound dehiscence (p < 0.001), and nerve injury (p < 0.001) when compared to patients who underwent OCTR. After matching, there was a significantly higher number of T2DM patients undergoing ECTR who had peripheral vascular disease (p = 0.045) and hypertension (p = 0.020) when compared to the OCTR group. These patients also had a lower incidence of fluid and electrolyte disorders (p = 0.002) and chronic blood loss anemia (p = 0.025). Conclusion: ECTR presents a superior choice for T2DM patients undergoing CTR, yielding significantly lower rates of wound infection, wound dehiscence, and nerve injury within 90 days post-surgery—reducing the risk by 31%, 48%, and 59%, respectively. These findings support the adoption of ECTR as the preferred method in this patient population, potentially leading to improved postoperative outcomes.Keywords: endoscopic treatment of carpal tunnel syndrome, open treatment of carpal tunnel syndrome, carpal tunnel syndrome, postoperative complications in patients with diabetes mellitus
Procedia PDF Downloads 69373 Automatic Differential Diagnosis of Melanocytic Skin Tumours Using Ultrasound and Spectrophotometric Data
Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene
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Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging
Procedia PDF Downloads 270372 Embedded Semantic Segmentation Network Optimized for Matrix Multiplication Accelerator
Authors: Jaeyoung Lee
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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network
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