Search results for: image system

Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

Abstract:

Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

Procedia PDF Downloads 513

Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

Procedia PDF Downloads 152

Authors: Sandhya Rao

Abstract:

Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.

Keywords: imageability, organizational patterns, legibility, cognitive mapping

Procedia PDF Downloads 312

Authors: Rajendar Kandan, Mohammad Zakaria Alli, Hong Ong

Abstract:

Cloud computing is a business model which provides an easier management of computing resources. Cloud users can request virtual machine and install additional softwares and configure them if needed. However, user can also request virtual appliance which provides a better solution to deploy application in much faster time, as it is ready-built image of operating system with necessary softwares installed and configured. Large numbers of virtual appliances are available in different image format. User can download available appliances from public marketplace and start using it. However, information published about the virtual appliance differs from each providers leading to the difficulty in choosing required virtual appliance as it is composed of specific OS with standard software version. However, even if user choses the appliance from respective providers, user doesn’t have any flexibility to choose their own set of softwares with required OS and application. In this paper, we propose a referenced architecture for dynamically customizing virtual appliance and provision them in an easier manner. We also add our experience in integrating our proposed architecture with public marketplace and Mi-Cloud, a cloud management software.

Keywords: cloud computing, marketplace, virtualization, virtual appliance

Procedia PDF Downloads 293

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

Abstract:

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 426

Authors: Nicholas V. Scott, Jack McCarthy

Abstract:

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

Procedia PDF Downloads 137

Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

Procedia PDF Downloads 367

Authors: M. G. R. S. Perera, B. S. Weerakoon, L. P. G. Sherminie, M. L. Jayatilake, R. D. Jayasinghe, W. Huang

Abstract:

The aim of this study was to measure and evaluate the Longitudinal Relaxation Times (T1) in bone marrow of an Acute Myeloid Leukaemia (AML) patient in order to explore the potential for a prognostic biomarker using Magnetic Resonance Imaging (MRI) which will be a non-invasive prognostic approach to AML. MR image data were collected in the DICOM format and MATLAB Simulink software was used in the image processing and data analysis. For quantitative MRI data analysis, Region of Interests (ROI) on multiple image slices were drawn encompassing vertebral bodies of L3, L4, and L5. T1 was evaluated using the T1 maps obtained. The estimated bone marrow mean value of T1 was 790.1 (ms) at 3T. However, the reported T1 value of healthy subjects is significantly (946.0 ms) higher than the present finding. This suggests that the T1 for bone marrow can be considered as a potential prognostic biomarker for AML patients.

Keywords: acute myeloid leukaemia, longitudinal relaxation time, magnetic resonance imaging, prognostic biomarker.

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Authors: Josephine Shamash, Stuart Smith

Abstract:

We examine reasons for introducing definitions in teaching mathematics in a number of different cases. We try to determine if, where, and when to provide a definition, and which definition to choose. We characterize different types of definitions and the different purposes we may have for formulating them, and detail examples of each type. Giving a definition at a certain stage can sometimes be detrimental to the development of the concept image. In such a case, it is advisable to delay the precise definition to a later stage. We describe two models, the 'successive approximation model', and the 'model of the extending definition' that fit such situations. Detailed examples that fit the different models are given based on material taken from a number of textbooks, and analysis of the way the concept is introduced, and where and how its definition is given. Our conclusions, based on this analysis, is that some of the definitions given may cause discontinuities in the learning sequence and constitute obstacles and unnecessary cognitive conflicts in the formation of the concept definition. However, in other cases, the discontinuity in passing from definition to definition actually serves a didactic purpose, is unavoidable for the mathematical evolution of the concept image, and is essential for students to deepen their understanding.

Keywords: concept image, mathematical definitions, mathematics education, mathematics teaching

Procedia PDF Downloads 128

Authors: Maria Pavlova

Abstract:

In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

Procedia PDF Downloads 217

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

Abstract:

Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

Procedia PDF Downloads 332

Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

Abstract:

The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

Procedia PDF Downloads 72

Authors: Sung Uk Ryu, Byoung Gook Jeon, Sung-Jae Yi, Dong-Jin Euh

Abstract:

In such passive safety injection systems in the nuclear power plant as Core Makeup Tank (CMT) and Hybrid Safety Injection Tank, various thermal-hydraulic phenomena including the direct contact condensation of steam and the thermal stratification of coolant occur. These phenomena are also closely related to the performance of the system. Depending on the condensation rate of the steam injected to the tank, the injection of the coolant and pressure equalizing timings of the tank are decided. The steam injected to the tank from the upper nozzle penetrates the coolant and induces a direct contact condensation. In the present study, the direct contact condensation of steam and the thermal mixing between the steam and coolant were examined by using the Particle Image Velocimetry (PIV) technique. Especially, by altering the size of the nozzle from which the steam is injected, the influence of steam injection velocity on the thermal mixing with coolant and condensation shall be comprehended, while also investigating the influence of condensation on the pressure variation inside the tank. Even though the amounts of steam inserted were the same in three different nozzle size conditions, it was found that the velocity of pressure rise becomes lower as the steam injection area decreases. Also, as the steam injection area increases, the thickness of the zone within which the coolant’s temperature decreases. Thereby, the amount of steam condensed by the direct contact condensation also decreases. The results derived from the present study can be utilized for the detailed design of a passive safety injection system, as well as for modeling the direct contact condensation triggered by the steam jet’s penetration into the coolant.

Keywords: passive safety injection systems, steam penetration, direct contact condensation, particle image velocimetry

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Authors: Teja Sai Puligadda

Abstract:

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

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

Procedia PDF Downloads 158

Authors: M. Owlia, M. H. Azarsa, M. Khabbazan, A. Mirbagheri

Abstract:

Proprioceptive neuromuscular facilitation exercises are a series of stretching techniques that are commonly used in rehabilitation and exercise therapy. Assessment of these exercises for true maneuvering requires extensive experience in this field and could not be down with patients themselves. In this paper, we developed software that uses Microsoft Kinect sensor, a spherical color marker, and real-time image processing methods to evaluate patient’s performance in generating true patterns of movements. The software also provides the patient with a visual feedback by showing his/her avatar in a Virtual Reality environment along with the correct path of moving hand, wrist and marker. Primary results during PNF exercise therapy of a patient in a room environment shows the ability of the system to identify any deviation of maneuvering path and direction of the hand from the one that has been performed by an expert physician.

Keywords: image processing, Microsoft Kinect, proprioceptive neuromuscular facilitation, upper extremities assessment, virtual reality

Procedia PDF Downloads 273

Authors: Aziz Ikhlef

Abstract:

Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

Procedia PDF Downloads 269

Authors: Hsiao-Yung Wang

Abstract:

This paper aims to elaborate methodology of visual rhetoric with constant reference to Mikhail Bakhtin’s concept of “chronotope”. First, it attempts to outline Ronald Barthes, the most representative scholar of visual rhetoric and structuralism, perspective on visual rhetoric and its time-space category by referring to the concurrent word-image, the symbolic systematicity, the outer dialogicity. Second, an alternative approach is explored for grasping the dynamics and functions of visual rhetoric by articulating Mikhail Bakhtin’s concept of “chronotope.” Furthermore, that visual rhetorical consciousness could be identified as “the meaning parabola which projects from word to image,” “the symbolic system which proceeds from sequence to disorder,” “the ideological environment which struggles from the local to the global.” Last but not least, primary vision of the 2014 Taipei LGBT parade would be analyzed preliminarily to evaluate the effectiveness and persuasiveness embodied by specific visual rhetorical strategies. How Bakhtin’s concept of “chronotope” to explain the potential or possible ideological struggle deployed by visual rhetoric might be interpreted empirically and extensively.

Keywords: barthes, chronotope, Mikhail Bakhtin, Taipei LGBT parade, visual rhetoric

Procedia PDF Downloads 471

Authors: Misha Alexander, S. B. Waykar

Abstract:

Visual Cryptography is a special unbreakable encryption technique that transforms the secret image into random noisy pixels. These shares are transmitted over the network and because of its noisy texture it attracts the hackers. To address this issue a Natural Visual Secret Sharing Scheme (NVSS) was introduced that uses natural shares either in digital or printed form to generate the noisy secret share. This scheme greatly reduces the transmission risk but causes distortion in the retrieved secret image through variation in settings and properties of digital devices used to capture the natural image during encryption / decryption phase. This paper proposes a new NVSS scheme that extracts the secret key from randomly selected unaltered multiple natural images. To further improve the security of the shares data hiding techniques such as Steganography and Alpha channel watermarking are proposed.

Keywords: decryption, encryption, natural visual secret sharing, natural images, noisy share, pixel swapping

Procedia PDF Downloads 403

Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

Abstract:

This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

Procedia PDF Downloads 81

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 112

Authors: Aziz Ikhlef

Abstract:

Most of multi-slices Computed Tomography (CT) scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This is translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80 kVp and 140 kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

Procedia PDF Downloads 193

Authors: Ankur Dixit, Hiroaki Wagatsuma

Abstract:

The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

Procedia PDF Downloads 172

Authors: Ching-Yi Huang, Pi-Fen Cheng, Hui-Zhu Chen, Shi Ting Huang, Heng-Hua Wang

Abstract:

This is a case of oral cancer after extensive resection and modified right lateral neck lymph node dissection followed by reconstruction with a skin flap. The nursing period lasted From September 25 to October 3, 2017, through observation, interview, physical assessment, and medical record review, the author identified the following nursing problems: acute pain, impaired oral mucous membrane, and body image change. During the nursing period, the author provided individual and overall nursing care and established mutual trust through the use of empathy. Author listened and eased the patient's physical indisposition, such as wound pain, we use medications and acupuncture massage to relieve pain. However, for oral mucosa change caused by surgery, provide continuous and complete oral care and oral exercise training to improve oral mucosal healing and restore swallowing function. In the body-image changes, guided him to express his feeling after the body-image change, and enhanced support and from the family, and encouraged him to attend head and neck cancer survivor alliance which allowed the patient to accept the altered body image and reaffirm self-worth. Hopefully, through sharing this nursing experience will help to the nursing care quality of nursing care for oral cancer patients after extensive resection and modified right lateral neck lymph node dissection followed by reconstruction with a skin flap.

Keywords: oral cancer, acute pain, impaired oral mucous membrane, body image change

Procedia PDF Downloads 185

Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

Abstract:

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

Procedia PDF Downloads 142

Authors: David Jurado, Carlos Ávila

Abstract:

Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

Procedia PDF Downloads 82

Authors: Ahmad Abdul-Razzak Aboudi Al-Issa

Abstract:

Thermal is the main important aspect in any hydraulic system since it is affected on the hydraulic system performance. Therefore must be simulated the hydraulic system -that was designed- in this aspect before constructing it. In this study, an existed expert system was using to simulate the thermal aspect of a designed hydraulic system that will be used in an industrial field. The expert system which is used in this study is (Hydraulic System Calculations), and its symbol (HSC). HSC had been designed and coded in an interactive program userfriendly named (Microsoft Visual Basic 2010).

Keywords: fluid power, hydraulic system, thermal and hydrodynamic, expert system

Procedia PDF Downloads 498

Authors: Syeda Shawana Mahasan, Muhammad Farooq Akhtar

Abstract:

The objective of this study is to analyze the influence of the green marketing mix strategy and corporate social responsibility (CSR) on the performance of an organization, taking into account the mediating effect of corporate image. The impact of frugal innovation and corporate activism is being examined. The data was gathered from executives at various levels of management, including top, middle, and lower-level managers, from a total of 550 manufacturing enterprises of different sizes, ranging from small to medium to large. The collected replies are processed and analyzed using SMART PLS version 4.0.0.0. The application of PLS-SEM demonstrates that the green marketing mix strategy and corporate social responsibility have a significant impact on organizational performance. Therefore, it is imperative for organizations to effectively adopt environmentally sustainable and socially conscious methods within their operations. The results indicate that the corporate image has a key role in mediating the relationship between the green marketing mix strategy, corporate social responsibility, and organizational performance. This demonstrates the imperative for organizations to actively enhance their favorable reputation among stakeholders. The combination of frugal innovation and corporate activism enhances the connection between corporate image and organizational performance. The current study assists managers in recognizing the significance of these particular constructs in maintaining the long-term performance of the organization.

Keywords: green marketing mix strategy, CSR, corporate image, organizational performance, frugal innovation, corporate activism

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Authors: Shu-Yu Hsu, Chen-Chien Hsu, Wei-Yen Wang

Abstract:

Color segmentation is a basic and simple way for recognizing the visual markers in a robotic tracking system. In this paper, we propose a new method for color segmentation by incorporating differential evolution algorithm and connected component labeling to autonomously preset the HSV threshold of visual markers. To evaluate the effectiveness of the proposed algorithm, a ROBOTIS OP2 humanoid robot is used to conduct the experiment, where five most commonly used color including red, purple, blue, yellow, and green in visual markers are given for comparisons.

Keywords: color segmentation, differential evolution, connected component labeling, humanoid robot

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Authors: Kumar Kanudkuri, A. Sandhya

Abstract:

Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality.

Keywords: ACR MRI phantom, MRI image quality metrics, SNRU, VIF, FSIM, GLCM, slice thickness accuracy, slice position accuracy

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Authors: Mohammad Shakir, Reshma Jolly, Mohammad Shoeb Khan, Noor-E-Iram

Abstract:

A nanocomposite system incorporating dextrin into nano-hydroxyapatite/chitin matrix (n-HA/DX/CT) has been successfully synthesized via co-precipitation route at room temperature for the application in bone tissue engineering by investigating biocompatibility, cytotoxicity and mechanical properties. The FTIR spectra of n-HA/DX/CT nanocomposite indicated a considerable intermolecular interaction between the various components of the system. The results of XRD, TEM and TGA/DTA revealed that the crystallinity, size and thermal stability of the n-HA/DX/CT scaffold has decreased and increased respectively. The result of SEM image of the n-HA/DX/CT scaffold indicated that the incorporation of dextrin affected the surface morphology while considerable in-vitro bioactivity has been observed in n-HA/DX/CT based on SBF study, referring a step towards possibility of making direct bond to living bone if implanted. Moreover, MTT assay suggested the non-toxic nature of n-HA/DX/CT to murine fibroblast L929 cells. The swelling study of n-HA/DX/CT scaffold indicated the low swelling rate for n-HADX/CT. All these results have paved the way for n-HA/DX/CT to be used as a competent material for bone tissue engineering.

Keywords: autograft, chitin, dextrin, nanocomposite

Procedia PDF Downloads 532