Search results for: collision tumor

Authors: Muhammad Hassan Khalil, Xu Jiadong

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Detection of malignant tumor inside the breast of women is a challenging field for the researchers. MWI (Microwave imaging) for breast cancer diagnosis has been of interest for last two decades, newly it suggested for finding cancerous tissues of women breast. A simple and basic idea of the mathematical modeling is used throughout this paper for imaging of malignant tumor. In this paper, the authors explained inverse scattering method in the microwave imaging and also present some simulation results.

Keywords: breast cancer detection, microwave imaging, tomography, tumor

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Authors: Ghada E. Esheba, Ghufran Kheshaifaty, Kholoud Al-Harbi, Wafa'a Al-Harbi, Ala'a Al-Orabi, Moayad Turkistani

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Krukenberg tumor is a rare metastatic ovarian carcinoma that usually occurs in female between 30 - 40 year old and rarely seen after menopause. Stomach is the most common primary site. Histopathological features of krukenberg tumors appear as diffuse stromal proliferation, mucus-production, and numerous signet-cells and these tumors spread mostly by lymphatic route. Treatment and prognostic factors are not well established. This study describes a 34 year old female with a unilateral ovarian mass discovered accidentally during cesarean section delivery and it was misdiagnosed as luteoma of pregnancy, but histopathological examination showed a diffuse infiltration of the ovary and omentum by signet ring cells. These findings were not correlated with luteoma of pregnancy or any other types of primary ovarian tumors like surface epithelial tumor, sex cord stromal tumor or germ cell tumor. However, after the analysis of immunohistochemical results (negative CK7, positive CK20 and CDX-2), the finding was the diagnostic of metastatic krukenberg tumor. Two weeks later, the patient was evaluated and a large gastric tumor was found in her stomach and she underwent gastrectomy.

Keywords: CK7, CK20, CDX-2, Krukenburg tumor, metastatic ovarian tumor

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Authors: N. Ghatwary, A. Ahmed, H. Jalab

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In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

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Authors: Sadia Arshad, Yifa Tang, Dumitru Baleanu

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A fractional order mathematical model is proposed that incorporate CD8+ cells, natural killer cells, cytokines and tumor cells. The tumor cells growth in the absence of an immune response is modeled by logistic law as it was the simplest form for which predictions also agreed with the experimental data. Natural Killer Cells are our first line of defense. NK cells directly kill tumor cells through several mechanisms, including the release of cytoplasmic granules containing perforin and granzyme, expression of tumor necrosis factor (TNF) family members. The effect of the NK cells on the tumor cell population is expressed with the product term. Rational form is used to describe interaction between CD8+ cells and tumor cells. A number of cytokines are produced by NKs, including tumor necrosis factor TNF, IFN, and interleukin (IL-10). Source term for cytokines is modeled by Michaelis-Menten form to indicate the saturated effects of the immune response. Stability of the equilibrium points is discussed for biologically significant values of bifurcation parameters. We studied the treatment of fractional order system by investigating analytical conditions of tumor eradication. Numerical simulations are presented to illustrate the analytical results.

Keywords: cancer model, fractional calculus, numerical simulations, stability analysis

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Authors: Zhen Peng, Baifeng Wu

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Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability

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Authors: Fakhrosadat Sajjadian, Ramin Ghasemi Shayan

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The tumor microenvironment plays an fundamental part in tumor start, movement, metastasis, and treatment resistance. It varies from ordinary tissue in terms of its extracellular network, vascular and lymphatic arrange, as well as physiological conditions. The clinical application of atomic cancer imaging is regularly prevented by the tall commercialization costs of focused on imaging operators as well as the constrained clinical applications and little showcase measure of a few operators. . Since numerous cancer types share comparable characteristics of the tumor microenvironment, the capacity to target these biomarkers has the potential to supply clinically translatable atomic imaging advances for numerous types encompassing cancer and broad clinical applications. Noteworthy advance has been made in focusing on the tumor microenvironment for atomic cancer imaging. In this survey, we summarize the standards and methodologies of later progresses in atomic imaging of the tumor microenvironment, utilizing distinctive imaging modalities for early discovery and conclusion of cancer. To conclude, The tumor microenvironment (TME) encompassing tumor cells could be a profoundly energetic and heterogeneous composition of safe cells, fibroblasts, forerunner cells, endothelial cells, flagging atoms and extracellular network (ECM) components.

Keywords: molecular, imaging, TME, medicine

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Authors: Zohra Salim

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Objective: To access the relationship of primary tumor thickness with cervical lymphadenopathy in squamous cell carcinoma of buccal mucosa. Methodology: A cross-sectional observational study was carried out on 80 Patients with biopsy-proven oral squamous cell carcinoma of buccal mucosa at Dow University of Health Sciences. All the study participants were treated with wide local excision of the primary tumor with elective neck dissection. Patients with prior head and neck malignancy or those with prior radiotherapy or chemotherapy were excluded from the study. Data was entered and analyzed on SPSS 21. Chi-squared test with 95% C.I and 80% power of the test was used to evaluate the relationship of tumor depth with cervical lymph nodes. Results: 50 participants were male, and 30 patients were female. 30 patients were in the age range of 20-40 years, 36 patients in the range of 40-60 years, while 14 patients were beyond age 60 years. Tumor size ranged from 0.3cm to 5cm with a mean of 2.03cm. Tumor depth ranged from 0.2cm to 5cm. 20% of the participants reported with tumor depth greater than 2.5cm, while 80% of patients reported with tumor depth less than 2.5cm. Out of 80 patients, 27 reported with negative lymph nodes, while 53 patients reported with positive lymph nodes. Conclusion: Our study concludes that relationship exists between the depth of primary tumor and cervical lymphadenopathy in squamous cell carcinoma of buccal mucosa.

Keywords: squamous cell carcinoma, tumor depth, cervical lymphadenopathy, buccal mucosa

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Authors: Guebli Abdelkader, Zerf Mohammed, Mekkades Moulay Idriss, BenGoua Ali, Atouti Nouredinne, Habchi Nawel

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The paper aims to show the influence of angles in the results of triple jump. Whereas our background confirms that a series of motions are characterized by complex angles in the properties phase (hop, step, and jump) as a combination of the pushed phase on ultimate phases in the result. For the purpose, our results are obtained from the National Athletics Championship 2013, which was filmed and analysis by the software kinovea. Based on the statistical analysis we confirm: there is a positive relationship between angle of the leg, hip angle, angle of the trunk in the collision during (hop, step, and jump), and there is a negative correlation to the angle of the knee relationship in a collision during.

Keywords: kinematics variables, the triple jump, the finale results, digital achievement

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Authors: Arturo Ayala-Hernandez, Humberto Hijar

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We propose a new alternative method for imposing fluid-solid boundary conditions in simulations of Multiparticle Collision Dynamics. Our method is based on the introduction of an explicit potential force acting between the fluid particles and a surface representing a solid boundary. We show that our method can be used in simulations of plane Poiseuille flows. Important quantities characterizing the flow and the fluid-solid interaction like the slip coefficient at the solid boundary and the effective viscosity of the fluid, are measured in terms of the set of independent parameters defining the numerical implementation. We find that our method can be used to simulate the correct hydrodynamic flow within a wide range of values of these parameters.

Keywords: Multiparticle Collision Dynamics, fluid-solid, boundary conditions, molecular dynamics

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Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

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In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

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Authors: Isaac Quiros-Fernandez, Angel Cid-Arregui

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Tumor-reactive T cell receptors (TCRs) are being subject of intense investigation since they offer great potential in adoptive cell therapies against cancer. However, the identification of tumor-specific TCRs has proven challenging, for instance, due to the limited expansion capacity of tumor-infiltrating T cells (TILs) and the extremely low frequencies of tumor-reactive T cells in the repertoire of patients and healthy donors. We have developed an approach for rapid identification and characterization of neoepitope-reactive TCRs from the T cell repertoire of healthy donors. CD8 T cells isolated from multiple donors are subjected to a first sorting step after staining with HLA multimers carrying the peptide of interest. The isolated cells are expanded for two weeks, after which a second sorting is performed using the same peptide-HLA multimers. The cells isolated in this way are then processed for single-cell sequencing of their TCR alpha and beta chains. Newly identified TCRs are cloned in appropriate expression vectors for functional analysis on Jurkat, NK92, and primary CD8 T cells and tumor cells expressing the appropriate antigen. We have identified TCRs specifically binding HLA-A2 presenting epitopes of tumor antigens, which are capable of inducing TCR-mediated cell activation and cytotoxicity in target cancer cell lines. This method allows the identification of tumor-reactive TCRs in about two to three weeks, starting from peripheral blood samples of readily available healthy donors.

Keywords: cancer, TCR, tumor antigens, immunotherapy

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Authors: Yusha'u Shu'aibu Baraya, Kah Keng Wong, Nik Soriani Yaacob

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Strobilanthes crispus (S. crispus), is a Malaysian herb locally known as ‘Pecah kaca’ or ‘Jin batu’ which have demonstrated potent anticancer effects in both in vitro and in vivo models. In particular, S. crispus subfraction (SCS) significantly reduced tumor growth in N-methyl-N-Nitrosourea-induced breast cancer rat model. However, there is paucity of information on the effects of SCS in breast cancer metastasis. Thus, in this study, the antimetastatic effects of SCS (100 mg/kg) was investigated following 30 days of treatment in 4T1-induced mammary tumor (n = 5) model. The response to treatment was assessed based on the outcome of the tumour growth, body weight and hematological parameters. The results demonstrated that tumor bearing mice treated with SCS (TM-S) had significant (p<0.05) reduction in the mean tumor number and tumor volume as well as tumor weight compared to the tumor bearing mice (TM), i.e. tumor untreated group. Also, there was no secondary tumor formation or tumor-associated lesions in the major organs of TM-S compared to the TM group. Similarly, comparable body weights were observed among the TM-S, normal (uninduced) mice treated with SCS and normal (untreated/control) mice (NM) groups compared to the TM group (p<0.05). Furthermore, SCS administration does not cause significant changes in the hematological parameters as compared to the NM group, which indicates no sign of anemia and toxicity related effects. In conclusion, SCS significantly inhibited the overall tumor growth and metastasis in 4T1-induced breast cancer mouse model suggesting its promising potentials as therapeutic agent for breast cancer treatment.

Keywords: 4T1-cells, breast cancer, metastasis, Strobilanthes crispus

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Authors: Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Madjid Soltani

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The computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, and drug extravasation from microvascular. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to show how capillary network structure induced by tumor affects drug delivery. The effect of heterogeneous capillary network induced by tumor on interstitial fluid flow and drug delivery is investigated by this multi scale method. The sprouting angiogenesis model is used for generating capillary network induced by tumor. Fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. The Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. Finally, convection-diffusion-reaction equation is used to simulate drug delivery. The dynamic approach which changes the capillary network structure based on signals sent by hemodynamic and metabolic stimuli is used in this study for more realistic assumption. The study indicates that drug delivery to solid tumors depends on the tumor induced capillary network structure. The dynamic approach generates the irregular capillary network around the tumor and predicts a higher interstitial pressure in the tumor region. This elevated interstitial pressure with irregular capillary network leads to a heterogeneous distribution of drug in the tumor region similar to in vivo observations. The investigation indicates that the drug transport properties have a significant role against the physiological barrier of drug delivery to a solid tumor.

Keywords: solid tumor, physiological barriers to drug delivery, angiogenesis, microvascular network, solute transport

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Authors: Chen Wang, Chun Liang

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Microsatellite instability (MSI) is characterized by high degree of polymorphism in microsatellite (MS) length due to a deficiency in mismatch repair (MMR) system. MSI is associated with several tumor types and its status can be considered as an important indicator for tumor prognostic. Conventional clinical diagnosis of MSI examines PCR products of a panel of MS markers using electrophoresis (MSI-PCR) which is laborious, time consuming, and less reliable. MSIpred, a python 2 package for automatic classification of MSI was released by this study. It computes important somatic mutation features from files in mutation annotation format (MAF) generated from paired tumor-normal exome sequencing data, subsequently using these to predict tumor MSI status with a support vector machine (SVM) classifier trained by MAF files of 1074 tumors belonging to four types. Evaluation of MSIpred on an independent 358-tumor test set achieved overall accuracy of over 98% and area under receiver operating characteristic (ROC) curve of 0.967. These results indicated that MSIpred is a robust pan-cancer MSI classification tool and can serve as a complementary diagnostic to MSI-PCR in MSI diagnosis.

Keywords: microsatellite instability, pan-cancer classification, somatic mutation, support vector machine

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Authors: Danish Farooq, Janos Juhasz

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Car-motorcycle accidents have been observed higher in recent years, which caused mainly riders’ fatalities and serious injuries. In-depth crash investigation methods aim to investigate the main factors which are likely involved in fatal road accidents and injury outcomes. The main objective of this study is to investigate the involved factors in car-motorcycle accidents in Budapest city. The procedure included statistical analysis and data sampling to identify car-motorcycle accidents by dominant accident types based on collision configurations. The police report was used as a data source for specified accidents, and simulation models were plotted according to scale (M 1:200). Car-motorcycle accidents were simulated in Virtual Crash software for 5 seconds before the collision. The simulation results showed that the main involved factors to car-motorcycle accidents were human behavior and view obstructions. The comprehensive, in-depth analysis also found that most of the car drivers and riders were unable to perform collision avoidance manoeuvres before the collision. This study can help the traffic safety authorities to focus on simulated involved factors to solve road safety issues in car-motorcycle accidents. The study also proposes safety measures to improve safe movements among road users.

Keywords: car motorcycle accidents, in-depth analysis, microscopic simulation, safety measures

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Authors: Adjal Yassine, Semmani Amar

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During the last decades, The risk of collision has been increased, especially in high maritime traffic. As the consequence, the demand is required for safety at sea and environmental protection. For this purpose, the consequences prediction of ship collisions is recommended in order to minimize structural failure. additionally, at the design stage of the ship, damage generated during the collision event must be taken into consideration. This structural failure, in some cases, can develop into the progressive collapse of other structural elements and generate catastrophic consequences. The present study investigates the progressive collapse of ships damaged by collisions using the Non -linear finite element method. The failure criteria are taken into account. The impacted area has a refined mesh in order to have more reliable results. Finally, a parametric study was conducted in this study to highlight the effect of the ship's speed, as well as the different impacted areas of double-bottom ships.

Keywords: collsion, strucural failure, ship, finite element analysis

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Authors: N. Sabiyath Fatima, R. K. Shanmugasundaram

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In Mobile Ad-hoc Networks (MANETS), every node performs both as transmitter and receiver. The existing backoff models do not exactly forecast the performance of the wireless network. Also, the existing models experience elevated packet collisions. Every time a collision happens, the station’s contention window (CW) is doubled till it arrives at the utmost value. The main objective of this paper is to diminish collision by means of contention window Multiplicative Increase Decrease Backoff (CWMIDB) scheme. The intention of rising CW is to shrink the collision possibility by distributing the traffic into an outsized point in time. Within wireless Ad hoc networks, the CWMIDB algorithm dynamically controls the contention window of the nodes experiencing collisions. During packet communication, the backoff counter is evenly selected from the given choice of [0, CW-1]. At this point, CW is recognized as contention window and its significance lies on the amount of unsuccessful transmission that had happened for the packet. On the initial transmission endeavour, CW is put to least amount value (C min), if transmission effort fails, subsequently the value gets doubled, and once more the value is set to least amount on victorious broadcast. CWMIDB is simulated inside NS2 environment and its performance is compared with Binary Exponential Backoff Algorithm. The simulation results show improvement in transmission probability compared to that of the existing backoff algorithm.

Keywords: backoff, contention window, CWMIDB, MANET

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Authors: Madhu Gupta, Vikas Sharma, Suresh P. Vyas

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CD13 receptors are abundantly overexpressed in tumor cells as well as in neovasculature. The CD13 receptors were selected as a targeted site and polymeric nanoparticles (NPs) as a targeted delivery system. By combining these, a cyclic NGR (cNGR) peptide ligand was coupled on the terminal end of polyethylene glycol-b-poly(lactic-co-glycolic acid) (PEG-b-PLGA) and prepared the dual targeted-NPs (cNGR-PEG-PTX-NPs) to enhance the intracellular delivery of anticancer drug to tumor cells and tumor endothelial cells via ligand-receptor interaction. In-vitro cytotoxicity studies confirmed that the presence of cNGR enhanced the cytotoxic efficiency by 2.8 folds in Human Umbilical Vein Endothelial (HUVEC) cells, while cytotoxicity was improved by 2.6 folds in human fibrosarcoma (HT-1080) cells as compared to non-specific stealth NPs. Compared with other tested NPs, cNGR-PEG-PTX-NPs revealed more cytotoxicity by inducing more apoptosis and higher intracellular uptake. The tumor volume inhibition rate was 59.7% in case of cNGR-PEG-PTX-NPs that was comparatively more with other formulations, indicating that cNGR-PEG-PTX-NPs could more effectively inhibit tumor growth. As a consequence, the cNGR-PEG-PTX-NPs play a key role in enhancing tumor therapeutic efficiency for treatment of CD13 receptor specific solid tumor.

Keywords: cyclic NGR, CD13 receptor, targeted polymeric NPs, solid tumor, intracellular delivery

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Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

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Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Nadine Wiesmann, Melanie Viel, Christoph Buhr, Rachel Tanner, Wolfgang Tremel, Juergen Brieger

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Recidivation of tumors and the development of resistances against the classical anti-tumor approaches represent a major challenge we face when treating cancer. In order to master this challenge, we are in desperate need of new treatment options beyond the beaten tracks. Zinc oxide nanoparticles (ZnO NPs) represent such an innovative approach. Zinc oxide is characterized by a high level of biocompatibility, concurrently ZnO NPs are able to exert anti-tumor effects. By concentration of the nanoparticles at the tumor site, tumor cells can specifically be exposed to the nanoparticles while low zinc concentrations at off-target sites are tolerated well and can be excreted easily. We evaluated the toxicity of ZnO NPs in vitro with the help of immortalized tumor cell lines and primary cells stemming from healthy tissue. Additionally, the Chorioallantoic Membrane Assay (CAM Assay) was employed to gain insights into the in vivo behavior of the nanoparticles. We could show that ZnO NPs interact with tumor cells as nanoparticulate matter. Furthermore, the extensive release of zinc ions from the nanoparticles nearby and within the tumor cells results in overload with zinc. Beyond that, ZnO NPs were found to further the generation of reactive oxygen species (ROS). We were able to show that tumor cells were more prone to the toxic effects of ZnO NPs at intermediate concentrations compared to fibroblasts. With the help of ZnO NPs covered by a silica shell in which FITC dye was incorporated, we were able to track ZnO NPs within tumor cells as well as within a whole organism in the CAM assay after injection into the bloodstream. Depending on the applied concentrations, selective tumor cell killing seems feasible. Furthermore, the combinational treatment of tumor cells with radiotherapy and ZnO NPs shows promising results. Still, further investigations are needed to gain a better understanding of the interaction between ZnO NPs and the human body to be able to pave the way for their application as an innovative anti-tumor agent in the clinics.

Keywords: metal oxide nanoparticles, nanomedicine, overcome resistances against classical treatment options, zinc oxide nanoparticles

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Authors: Sarah K. Hagi, Majdi Alnowaimi

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In the last decade, there were immense advancements in the medical imaging modalities. These advancements can scan a whole volume of the lung organ in high resolution images within a short time. According to this performance, the physicians can clearly identify the complicated anatomical and pathological structures of lung. Therefore, these advancements give large opportunities for more advance of all types of lung cancer treatment available and will increase the survival rate. However, lung cancer is still one of the major causes of death with around 19% of all the cancer patients. Several factors may affect survival rate. One of the serious effects is the breathing process, which can affect the accuracy of diagnosis and lung tumor treatment plan. We have therefore developed a semi automated algorithm to localize the 3D lung tumor positions across all respiratory data during respiratory motion. The algorithm can be divided into two stages. First, a lung tumor segmentation for the first phase of the 4D computed tomography (CT). Lung tumor segmentation is performed using an active contours method. Then, localize the tumor 3D position across all next phases using a 12 degrees of freedom of an affine transformation. Two data set where used in this study, a compute simulate for 4D CT using extended cardiac-torso (XCAT) phantom and 4D CT clinical data sets. The result and error calculation is presented as root mean square error (RMSE). The average error in data sets is 0.94 mm ± 0.36. Finally, evaluation and quantitative comparison of the results with a state-of-the-art registration algorithm was introduced. The results obtained from the proposed localization algorithm show a promising result to localize alung tumor in 4D CT data.

Keywords: automated algorithm , computed tomography, lung tumor, tumor localization

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Authors: Bo-Huei Huang, Chih-Hsun Yang, Meng-Tsan Tsai

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Optical coherence tomography (OCT) enables to provide advantages of noninvasive imaging, high resolution, and high imaging speed. In this study, we integrated OCT and a CW laser for tumor diagnosis and treatment. The axial and transverse resolutions of the developed OCT system are 3 μm and 1 μm, respectively. The frame rate of OCT system is 30 frames/s. In this study, the tumor cells were implanted into the mice skin and scanned by OCT to observe the morphological and angiographic changes. With OCT imaging, 3D microstructures and skin angiography of mice skin can be simultaneously acquired, which can be utilized for identification of the tumor distribution. Then, the CW laser beam can be accurately controlled to expose on the center of the tumor, according to the OCT results. Moreover, OCT was used to monitor the induced photothermolysis and to evaluate the treatment outcome. The results showed that OCT-guided laser therapy could efficiently improve the treatment outcome and the extra damage induced by CW can be greatly reduced. Such OCT-guided laser therapy system could be a potential tool for dermatological applications.

Keywords: optical coherence tomography, laser therapy, skin tumor, position guide

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Sandabad Sara, Sayd Tahri Yassine, Hammouch Ahmed

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The development of science has allowed computer scientists to touch the medicine and bring aid to radiologists as we are presenting it in our article. Our work focuses on the detection and localization of tumors areas in the human brain; this will be a completely automatic without any human intervention. In front of the huge volume of MRI to be treated per day, the radiologist can spend hours and hours providing a tremendous effort. This burden has become less heavy with the automation of this step. In this article we present an automatic and effective tumor detection, this work consists of two steps: the first is the image filtering using the filter Nl-means, then applying the expectation maximization algorithm (EM) for retrieving the tumor mask from the brain MRI and extracting the tumor area using the mask obtained from the second step. To prove the effectiveness of this method multiple evaluation criteria will be used, so that we can compare our method to frequently extraction methods used in the literature.

Keywords: MRI, Em algorithm, brain, tumor, Nl-means

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

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

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

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Authors: Mohammad Ali Hasanzadeh, Thierry Van Elslander, Eddy Van De Voorde

Abstract:

About 90 percent of world merchandise trade by volume being carried by sea. Maritime transport remains as back bone behind the international trade and globalization meanwhile all seaborne goods need using at least two ports as origin and destination. Amid seaborne traded cargos, container traffic is a prosperous market with about 16% in terms of volume. Albeit containerized cargos are less in terms of tonnage but, containers carry the highest value cargos amongst all. That is why efficient handling of containers in ports is very important. Accidents are the foremost causes that lead to port inefficiency and a surge in total transport cost. Having different port safety management systems (PSMS) in place, statistics on port accidents show that numerous accidents occur in ports. Some of them claim peoples’ life; others damage goods, vessels, port equipment and/or the environment. Several accident investigation illustrate that the most common accidents take place throughout transport operation, it sometimes accounts for 68.6% of all events, therefore providing a safer workplace depends on reducing collision risk. In order to quantify risks at the port area different variables can be used as exposure measurement. One of the main motives for defining and using exposure in studies related to infrastructure is to account for the differences in intensity of use, so as to make comparisons meaningful. In various researches related to handling containers in ports and intermodal terminals, different risk exposures and also the likelihood of each event have been selected. Vehicle collision within the port area (10-7 per kilometer of vehicle distance travelled) and dropping containers from cranes, forklift trucks, or rail mounted gantries (1 x 10-5 per lift) are some examples. According to the objective of the current research, three categories of accidents selected for collision risk assessment; fall of container during ship to shore operation, dropping container during transfer operation and collision between vehicles and objects within terminal area. Later on various consequences, exposure and probability identified for each accident. Hence, reducing collision risks profoundly rely on picking the right risk exposures and probability of selected accidents, to prevent collision accidents in container terminals and in the framework of risk calculations, such risk exposures and probabilities can be useful in assessing the effectiveness of safety programs in ports.

Keywords: container terminal, collision, seaborne trade, risk exposure, risk probability

Procedia PDF Downloads 348

Authors: Ji-il Park, Min Kyu Yu, Jong-woo Lee, Sam-hyeon Yoo

Abstract:

The purpose of this research is to analyze the gait strategy between the normal and loaded gait. To this end, five male participants satisfied two conditions: the normal and loaded gait (backpack load 25.2 kg). As expected, results showed that additional loads elicited not a proportional increase in vertical and shear ground reaction force (GRF) parameters but also increase of the impulse, momentum and mechanical work. However, in case of the loaded gait, the time duration of the double support phase was increased unexpectedly. It is because the double support phase which is more stable than the single support phase can reduce instability of the loaded gait. Also, the directions of the pre-collision and after-collision were moved upward and downward compared to the normal gait. As a result, regardless of the additional backpack load, the impulse-momentum diagram during the step-to-step transition was maintained such as the normal gait. It means that human walk efficiently to keep stability and minimize total net works in case of the loaded gait.

Keywords: normal gait, loaded gait, impulse, collision, gait analysis, mechanical work, backpack load

Procedia PDF Downloads 269

Authors: M. Saeed, A. Shahidzadeh

Abstract:

Interaction between teachers and learners requires applying a set of samples (examples) which helps to create coordination between the goals and methods. The main result and achievement and application of samples (examples) are that they can bring the teacher and learner to a shared understanding of the concept. mathematical concepts, and also one of the challenging issues in the discussion of the function is to find the collision points of functions of and, regarding that the example space of teachers is different in this issue, this paper aims to present an example space including several problems of the secondary school with the help of intuition and drawing various graphs of functions of and for more familiarity of teachers.

Keywords: inverse function, educational example, Mathematic example, example space

Procedia PDF Downloads 154

Authors: Ruqia Nazir, Robin Perutz

Abstract:

Collision-induced dissociation (CID) can be used to study the intrinsic properties of ions in the gas phase.1 Decay pathways of transition metal difluoride complexes of titanium, zirconium, hafnium, and ruthenium were studied by CID in an ESI-Ion trap mass spectrometer. Furthermore, the decay pathways of multiply charged anions (MCAs) of titanium and zirconium were also studied. The CID results are illustrated by the behaviour of (Cp*)₂TiF₂, which initially forms the ions [M-F-]⁺, [M+Na]⁺, and [M+K]⁺. The [(Cp*₂)TiF⁺ ion decays on resonant excitation to lose HF forming [Cp*(C₅Me₄CH₂)Ti]⁺ (Figure). The other major ion, [(Cp*)₂TiF₂+Na]⁺, decays on resonant excitation with production of [(Cp*)₂TiF₂]⁺ and [C₅Me₄CH₂]⁺. We also report the behaviour of Cp₂MF₂ (M = Zr, Hf) and Ru(PMe₃)₄F₂. The decay pathway of the multiply charged anions (MCAs), notably TiF₆²⁻ and ZrF₆²⁻ was concluded to be ionic fragmentation with loss of F⁻ rather than electron detachment.

Keywords: collision induced dissociation, transition metal difluoride comolexes, multiply charged anions, mass spectrometry

Procedia PDF Downloads 79