Search results for: superior capsule reconstruction

Authors: Majid Khan

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Introduction: In this era of microsurgery, free flap holds a remarkable spot in reconstructive surgery. A free flap is well suited for composite defects as it provides sufficient and well-vascularized tissue for coverage. We report our experience with the use of the free flaps for the reconstruction of composite defects. Methods: This is a retrospective case series (chart review) of patients who underwent reconstruction of composite defects with a free flap at Aga Khan University Hospital, Karachi (Pakistan) from January 01, 2015, to December 31, 2019. Data were collected for patient demographics, size of the defect, size of flap, recipient vessels, postoperative complications, and outcome of the free flap. Results: Over this period, 532 free flaps are included in this study. The overall success rate is 95.5%. The mean age of the patient was 44.86 years. In 532 procedures, there were 448 defects from tumor ablation of head and neck cancer. The most frequent free flap was the anterolateral thigh flap in 232 procedures. In this study, the risk factor hypertension (p=0.004) was found significant for wound dehiscence, preop radiation/chemotherapy (p=0.003), and malnutrition (p=0.005) were found significant for fistula formation. Malnutrition (p=0.02) and use of vein grafts (p=0.025) were significant factors for flap failure. Conclusion: Free tissue transfer is a reliable option for the reconstruction of large and composite defects. Hypertension, malnutrition, and preoperative radiotherapy can cause significant morbidity.

Keywords: free flap, free flap failure, risk factors for flap failure, free flap outcome

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Authors: Donghun Jeong, Somyoung Shin, Yeoil Yun

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A large-scale traffic accident refers to an accident in which more than three people die or more than thirty people are dead or injured. In order to prevent a large-scale traffic accident from causing a big loss of lives or establish effective improvement measures, it is important to analyze accident situations in-depth and understand the effects of major accident variables on an accident. This study aims to analyze the contribution of individual accident variables to accident results, based on the accurate reconstruction of traffic accidents using PC-Crash’s Multi-Body, which is an accident reconstruction program, and simulation of each scenario. Multi-Body system of PC-Crash accident reconstruction program is used for multi-body accident reconstruction that shows motions in diverse directions that were not approached previously. MB System is to design and reproduce a form of body, which shows realistic motions, using several bodies. Targeting the 'freight truck cargo drop accident around the Changwon Tunnel' that happened in November 2017, this study conducted a simulation of the freight truck cargo drop accident and analyzed the contribution of individual accident majors. Then on the basis of the driving speed, cargo load, and stacking method, six scenarios were devised. The simulation analysis result displayed that the freight car was driven at a speed of 118km/h(speed limit: 70km/h) right before the accident, carried 196 oil containers with a weight of 7,880kg (maximum load: 4,600kg) and was not fully equipped with anchoring equipment that could prevent a drop of cargo. The vehicle speed, cargo load, and cargo anchoring equipment were major accident variables, and the accident contribution analysis results of individual variables are as follows. When the freight car only obeyed the speed limit, the scattering distance of oil containers decreased by 15%, and the number of dropped oil containers decreased by 39%. When the freight car only obeyed the cargo load, the scattering distance of oil containers decreased by 5%, and the number of dropped oil containers decreased by 34%. When the freight car obeyed both the speed limit and cargo load, the scattering distance of oil containers fell by 38%, and the number of dropped oil containers fell by 64%. The analysis result of each scenario revealed that the overspeed and excessive cargo load of the freight car contributed to the dispersion of accident damage; in the case of a truck, which did not allow a fall of cargo, there was a different type of accident when driven too fast and carrying excessive cargo load, and when the freight car obeyed the speed limit and cargo load, there was the lowest possibility of causing an accident.

Keywords: accident reconstruction, large-scale traffic accident, PC-Crash, MB system

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Authors: Shilkin A.G., Goncharov D.V., Rotanov D.A., Voitecha M.A., Kulyagina Y.I., Mochalova U.E.

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Context: Phacoemulsification is a surgical technique used to remove cataracts, but it has a higher number of complications when dense cataracts are present. The risk factors include thin posterior capsule, dense nucleus fragments, and prolonged exposure to high-power ultrasound. To minimize these complications, various methods are used. Research aim: The aim of this study is to develop and implement optimal methods of ultrasound phacoemulsification for dense cataracts in order to minimize postoperative complications. Methodology: The study involved 36 eyes of dogs with dense cataracts over a period of 5 years. The surgeries were performed using a LEICA 844 surgical microscope and an Oertli Faros phacoemulsifier. The surgical techniques included the optimal technique for breaking the nucleus, bimanual surgery, and the use of Akahoshi prechoppers. Findings: The complications observed during the surgery included rupture of the posterior capsule and the need for anterior vitrectomy. Complications in the postoperative period included corneal edema and uveitis. Theoretical importance: This study contributes to the field by providing insights into the special features of phacoemulsification for dense cataracts. It highlights the importance of using specific techniques and settings to minimize complications. Data collection and analysis procedures: The data for the study were collected from surgeries performed on dogs with dense cataracts. The complications were documented and analyzed. Question addressed: The study addressed the question of how to minimize complications during phacoemulsification surgery for dense cataracts. Conclusion: By following the optimal techniques, settings, and using prechoppers, the surgery for dense cataracts can be made safer and faster, minimizing the risks and complications.

Keywords: dense cataracts, phacoemulsification, phacoemulsification of cataracts in elderly dogs, осложнения факоэмульсификации

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Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

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Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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Authors: Syafril Hendrik Hutabarat, Hartiwiningsih, Pujiyono Suwadi

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The Financial Service Authority (FSA) was formed as a response to the 1997 monetary crisis and the 2008 financial crisis so that it was more defensive in nature while developments in information and communication technology have required state policies to be more offensive to keep up with times. Reconstruction of Authorities of the FSA's Investigator is intended to keep the agency worthy to be part of an integrated criminal justice system in Indonesia which has implications for expanding its authority in line with efforts to protect and increase the welfare of the people. The results show that internal synergy between sub-sectors in the financial services sector is not optimised, some are even left behind so that the FSA is not truly an authority in the financial services sector. This research method is empirical. The goal of synergy must begin with internal synergy which has its moment when Indonesia gets a demographic bonus in the 2030s and becomes an international logistics hub supported by the national financial services sector.

Keywords: reconstruction, authorities, FSA investigators, synergy, demography

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Authors: Andrew Tan Hwee Chye, Yeo Zhen Ning

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This study aims to meta-analyse clinical studies comparing femoral tunnel position (FTP), femoral tunnel length (FTL) and graft bending angle (GBA) of single-bundle Anterior Cruciate Ligament (ACL) reconstruction using Transtibial (TT), Anteromedial (AM) and Outside-in (OI) techniques. A meta-analysis comparing the FTP, FTL and GBA of single-bundle ACL reconstruction utilising the TT, AM and OI was performed. Prospective Comparative Studies (PCS) and Retrospective Comparative Studies (RCS) from PubMed, Cochrane Library, and Embase were included. A total of 17 studies were included in this study. TT had the longest FTL, when compared to AM (Mean difference = 7.38, 95% CI: 3.76 to 11.00, P < 0.001) and OI (Mean difference = 9.47, 95% CI: 4.89 to 14.05, P < 0.001). In the deep-to-shallow direction, the OI resulted in a significantly deeper femoral tunnel as compared to the TT (Mean difference = 4.36, 95% CI: 1.39 to 7.33, P = 0.004) (Figure 6B). The AM technique also contributed to a significantly lower tunnel position as compared to the OI technique (Mean difference = 2.34, 95% CI: 0.76 to 3.92, P = 0.004). There were no significant differences in the graft bending angle between TT, AM and OI techniques. AM and OI techniques provide a more anatomical position as compared to the TT. Although FTL in the TT is longer than the AM and OI, all three techniques exceed the critical length of 25mm. There are no differences in the GBA between the three techniques.

Keywords: femoral tunnel position, femoral tunnel length, anterior cruciate ligament, transtibial, graft bending angle, anteromedial, outside-in

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Po-Hao Huang, Pei-Ju Chiang

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The structured light 3D scanner is commonly used for measuring the 3D shape of an object. Through projecting designed light patterns on the object, deformed patterns can be obtained and used for the geometric shape reconstruction. At present, Gray code is the most reliable and commonly used light pattern in the structured light 3D scanner. However, the trade-off between scanning efficiency and accuracy is a long-standing and challenging problem. The design of light patterns plays a significant role in the scanning efficiency and accuracy. Thereby, we proposed a novel encoding method integrating color information and Gray-code to improve the scanning efficiency. We will demonstrate that with the proposed method, the scanning time can be reduced to approximate half of the one needed by Gray-code without reduction of precision.

Keywords: gray-code, structured light scanner, 3D shape acquisition, 3D reconstruction

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Authors: Ines Elouedi, Atef Hammouda

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This paper presents a new fast version of the generalized Multi-Directional Radon Transform method. The new method uses the inverse Fast Fourier Transform to lead to a faster Generalized Radon projections. We prove in this paper that the fast algorithm leads to almost the same results of the eldest one but with a considerable lower time computation cost. The projection end result of the fast method is a parameterized Radon space where a high valued pixel allows the detection of a curve from the original image. The proposed fast inversion algorithm leads to an exact reconstruction of the initial image from the Radon space. We show examples of the impact of this algorithm on the pattern recognition domain.

Keywords: fast generalized multi-directional Radon transform, curve, exact reconstruction, pattern recognition

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Authors: Ruhizal Roosli, Julaihi Wahid, Abu Hassan Abu Bakar, Faizal Baharum

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This paper reports on the progress of a study on the reconstruction project after the ‘Yellow Flood’ disaster in Kelantan, Malaysia. Malaysia still does not have guidelines to build housing after a disaster especially in disaster-prone areas. At the international level, many guidelines have been prepared that is found suitable for post-disaster housing. Which guidelines can be adapted that best describes the situation in Malaysia? It was reported that the houses should be built on stilts, which can withstand certain level of impact during flooding. Unfortunately, until today no specific guideline was available to assist homeowners to rebuild their homes after disaster. In addition, there is also no clear operational procedure to monitor the progress of this construction work. This research is an effort to promoting resilient housing; safety and security; and secure tenure in a prone area. At the end of this study, key lessons will be emerged from the review process and data analysis. These inputs will then have influenced to the content that will be developed and presented as guidelines. An overall objective is to support humanitarian responses to disaster and conflicts for resilience house construction to flood prone area. Interviews with the field based staff were from recent post-disaster housing workforce (disaster management mechanism in Malaysia especially in Kelantan). The respondents were selected based on their experiences in disaster response particularly related to housing provision. These key lessons are perhaps the best practical (operational and technical) guidelines comparing to other International cases to be adapted to the national situations.

Keywords: disaster, guideline, housing, Malaysia, reconstruction

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: Duško Salemović, Aleksandar Dedić, Matilda Lazić, Dragan Halas

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The aim of the paper was the thermal balance control of vertical kiln dryer indirect type (VSU-36) for drying sunflower seed, produced by "Cer" - Čačak, capacity 39 [t/h]. The balance control was executed because the dryer damaged by NATO bombing in 1999, and it was planned its reconstruction. The structural and geometric characteristics of the dryer were known, and it was necessary to determine the parameters of: wet air as a drying agent and the sunflower seeds. The thermal balance control was the basis for replacement of damaged parts of dryer during its reconstruction. After that, it was necessary to perform the subsequent calculation of strength. Therefore, since its accuracy was largely dependent on cost-effectiveness and safety of a single drying chamber. Also, the work provides guidelines for the regimes of drying of grain crops with the explanation of specificity of drying sunflowers.

Keywords: sunflower seeds, regimes of drying, vertical kiln dryer, thermal analysis

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Authors: Tal Remez, Or Litany, Alex Bronstein

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The pursuit of smaller pixel sizes at ever increasing resolution in digital image sensors is mainly driven by the stringent price and form-factor requirements of sensors and optics in the cellular phone market. Recently, Eric Fossum proposed a novel concept of an image sensor with dense sub-diffraction limit one-bit pixels (jots), which can be considered a digital emulation of silver halide photographic film. This idea has been recently embodied as the EPFL Gigavision camera. A major bottleneck in the design of such sensors is the image reconstruction process, producing a continuous high dynamic range image from oversampled binary measurements. The extreme quantization of the Poisson statistics is incompatible with the assumptions of most standard image processing and enhancement frameworks. The recently proposed maximum-likelihood (ML) approach addresses this difficulty, but suffers from image artifacts and has impractically high computational complexity. In this work, we study a variant of a sensor with binary threshold pixels and propose a reconstruction algorithm combining an ML data fitting term with a sparse synthesis prior. We also show an efficient hardware-friendly real-time approximation of this inverse operator. Promising results are shown on synthetic data as well as on HDR data emulated using multiple exposures of a regular CMOS sensor.

Keywords: binary pixels, maximum likelihood, neural networks, sparse coding

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Authors: Muhammad Waqas

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In this competitive environment, organizations in the service sector and industrial sector are trying their best to win the loyalty of their customers by providing superior quality services and innovative products to remain competitive in the market. The objective of this study is to focus on the concept that public dealing and tripping of electricity have a significant impact on customer satisfaction. This study is focused on the banking sector. It is concluded that quality in service sectors strongly depends on employees' commitment to the organization for providing superior services to the customers to enhance customers' satisfaction.

Keywords: customer complaints, banking sector, customer satisfaction, Islamic banking

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Authors: N. V. V. S. D. Prasad

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Field experiments were conducted at Regional Agricultural Research Station, Lam, Guntur, Andhra Pradesh, India for two seasons during 2011-13 to evaluate the efficacy of flupyradifurone SL 200 a new class of insecticide in butenolide group against leaf hoppers, aphids and whitefly in Cotton. The test insecticide flupyradifurone 200 was evaluated at three doses @ 150, 200 and 250 g ai/ha ha along with imidacloprid 200 SL @ 20g ai/ha, acetamiprid 20 SP @ 20g ai/ha, thiamethoxam 25 WG @ 25g ai/ha and monocrotophos 36 SL @ 360 g ai/ha as standards. Flupyradifurone SL 200 even at lower dose of 150g ai/ha exhibited superior efficacy against cotton leafhopper, Amrasca devastans than the neonicotinoids which are widely used for control of sucking pests in cotton. Against cotton aphids, Aphis gossypii. Flupyradifurone SL 200 @ 200 and 250 g ai/ha ha was proved to be effective and the lower dose @ 150g ai/ha performed better than some of the neonicotinoids. The effect of flupyradifurone SL 200 on cotton against whitefly, Bemisia tabaci was evident at higher doses of 200 and 250 g ai/ha and superior to all standard treatments, however, the lower dose is at par with neonicotinoids. The seed cotton yield of flupyradifurone 200 SL at all the doses tested was superior than imidacloprid 200 SL @ 20g ai/ha and acetamiprid 20 SP @ 20g ai/ha. There is no significant difference among the insecticidal treatments with regards to natural enemies. The results clearly suggest that flupyradifurone is a new tool to combat sucking pest problems in cotton and can well fit in IRM strategies in light of wide spread insecticide resistance in cotton sucking pests.

Keywords: cotton, flupyradifurone, neonicotinoids, sucking pests

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Authors: Ting Gao, Mingyue He

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Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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Authors: Alireza Akbari, Gelareh Babaee Khou

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Ground Penetrating Radar (GPR) is an important nondestructive remote sensing tool that has been used in both military and civilian fields. Recently, GPR imaging has attracted lots of attention in detection of subsurface shallow small targets such as landmines and unexploded ordnance and also imaging behind the wall for security applications. For the monostatic arrangement in the space-time GPR image, a single point target appears as a hyperbolic curve because of the different trip times of the EM wave when the radar moves along a synthetic aperture and collects reflectivity of the subsurface targets. With this hyperbolic curve, the resolution along the synthetic aperture direction shows undesired low resolution features owing to the tails of hyperbola. However, highly accurate information about the size, electromagnetic (EM) reflectivity, and depth of the buried objects is essential in most GPR applications. Therefore hyperbolic curve behavior in the space-time GPR image is often willing to be transformed to a focused pattern showing the object's true location and size together with its EM scattering. The common goal in a typical GPR image is to display the information of the spatial location and the reflectivity of an underground object. Therefore, the main challenge of GPR imaging technique is to devise an image reconstruction algorithm that provides high resolution and good suppression of strong artifacts and noise. In this paper, at first, the standard back-projection (BP) algorithm that was adapted to GPR imaging applications used for the image reconstruction. The standard BP algorithm was limited with against strong noise and a lot of artifacts, which have adverse effects on the following work like detection targets. Thus, an improved BP is based on cross-correlation between the receiving signals proposed for decreasing noises and suppression artifacts. To improve the quality of the results of proposed BP imaging algorithm, a weight factor was designed for each point in region imaging. Compared to a standard BP algorithm scheme, the improved algorithm produces images of higher quality and resolution. This proposed improved BP algorithm was applied on the simulation and the real GPR data and the results showed that the proposed improved BP imaging algorithm has a superior suppression artifacts and produces images with high quality and resolution. In order to quantitatively describe the imaging results on the effect of artifact suppression, focusing parameter was evaluated.

Keywords: algorithm, back-projection, GPR, remote sensing

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Authors: Radwa E. Sweif, Amira A. A. Abdallah

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Background: Evaluation of gait efficiency is used to examine energy consumption especially in patients with movement disorders. Hypothesis/Purpose: This study compared the physiological and mechanical measures of gait efficiency between patients with ACL reconstruction (ACLR) and healthy controls and correlated among these measures. Methods: Seventeen patients with ACLR and sixteen healthy controls with mean ± SD age 23.06±4.76 vs 24.85±6.47 years, height 173.93±6.54 vs 175.64±7.37cm, and weight 74.25±12.1 vs 76.52±10.14 kg, respectively, participated in the study. The patients were operated on six months prior to testing. They should have completed their accelerated rehabilitation program during this period. A 3D motion analysis system was used for collecting the mechanical measures (Biomechanical Efficiency Quotient (BEQ), the maximum degree of knee internal rotation during stance phase and speed of walking). The physiological measures (Physiological Cost Index (PCI) and Rate of Perceived Exertion (RPE)) were collected after performing the 6- minute walking test. Results: MANOVA showed that the maximum degree of knee internal rotation, PCI, and RPE increased and the speed decreased significantly (p<0.05) in the patients compared with the controls with no significant difference for the BEQ. Finally, there were significant (p<0.05) positive correlations between each of the PCI & RPE and each of the BEQ, speed of walking and the maximum degree of knee internal rotation in each group. Conclusion: It was concluded that there are alterations in both mechanical and physiological measures of gait efficiency in patients with ACLR after being rehabilitated, clarifying the need for performing additional endurance as well as knee stability training programs. Moreover, the positive correlations indicate that using either of the mechanical or physiological measures for evaluating gait efficiency is acceptable.

Keywords: ACL reconstruction, mechanical, physiological, gait efficiency

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Authors: Shahriar Farzam, Maryam Rastgarpour

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Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: curvelet transform, CBCT, image enhancement, image denoising

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Authors: Abdullah Saeidi, Aydin Gülses, Christan Flörke

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Skin cancer of the face region is the most common type of malignancy and surgical excision is the preferred approach. However, the clinical long term results reported in the literature are still controversial. Objectives: To describe; 1. Demographical characteristics 2. Affected site, distribution and TNM classification regarding tumor type 3. Surgical aspects • Surgical removal: excision principles, safety margins, the need for secondary resection, primary reconstruction/ defect closure, anesthesia protocol, duration of hospital stay (if any) • Secondary intervention for defect closure/reconstruction: Flap technique, anesthesia protocol, duration of hospital stay (if any), postoperative wound management etc. 4. Tumor recurrences 5. Clinical outcomes 6. Studying the possible therapy approach throw Biostatistical relation and correlation between multiple Histological, diagnostics and clinical Faktors. following surgical ablation of the skin cancer of the head and neck region. Methods: Selection and statistical analysis of medical records of patients who had admitted to the Department of Oral and Maxillofacial Surgery, Universitätsklinikum Schleswig Holstein, Campus Kiel during the period of 2015-2019 will be retrospectively evaluated. Data will be collected via ORBIS Information-Management-System (ORBIS AG, Saarbrücken, Germany).

Keywords: non melanoma skin cancer, face skin cancer, skin reconstruction, non melanoma skin cancer recurrence, non melanoma skin cancer metastases

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Authors: Liu Mingxin

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Streets act as the organizers of each image element on the urban spatial route, and the spatial continuity of urban streets is the basis for people to perceive the overall image of the city. This paper takes the walking space of Zhengzhou city as the research object, conducts investigation and analysis through questionnaire interviews, and selects typical walking space for in-depth study. Through the analysis of questionnaire data, the investigation and analysis of the current situation of walking space, and the analysis of pedestrian psychological behavior activities, the paper summarizes the construction suggestions of urban walking space continuity from the three aspects of the composition of walking street, the bottom interface and side interface, and the service facilities of walking space. The walking space is not only the traffic space but also the comfortable experience and the continuity of the space.

Keywords: walking space, spatial continuity, walking psychology, space reconstruction

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Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 45

Authors: R. Ranjith Kumar

Abstract:

Computer modeling and simulation of human movement is playing an important role in sports and rehabilitation. Accurate modeling and analysis of human knee join is more complex because of complicated structure whose geometry is not easily to represent by a solid model. As part of this project, from the number of CT scan images of human knee join surface reconstruction is carried out using 3D slicer software, an open source software. From this surface reconstruction model, using mesh lab (another open source software) triangular meshes are created on reconstructed surface. This final triangular mesh model is imported to Solid Works, 3D mechanical CAD modeling software. Finally this CAD model is imported to ABAQUS, finite element analysis software for analyzing the knee joints. The results obtained are encouraging and provides an accurate way of modeling and analysis of biological parts without human intervention.

Keywords: solid works, CATIA, Pro-e, CAD

Procedia PDF Downloads 102

Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

Abstract:

We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

Procedia PDF Downloads 277

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 61

Authors: Krzysztof Malczewski

Abstract:

Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

Procedia PDF Downloads 399

Authors: Shreyash Hadke, Manendra Singh Parihar, Rajesh Khatirkar

Abstract:

In the present investigation, the variation in the microstructure with the changes in the heat treatment conditions i.e. temperature and time was observed. Ti-6Al-4V alloy was subject to solution annealing treatments in β (1066C) and α+β phase (930C and 850C) followed by quenching, air cooling and furnace cooling to room temperature respectively. The effect of solution annealing and cooling on the microstructure was studied by using optical microscopy (OM), scanning electron microscopy (SEM), electron backscattered diffraction (EBSD) and x-ray diffraction (XRD). The chemical composition of the β phase for different conditions was determined with the help of energy dispersive spectrometer (EDS) attached to SEM. Furnace cooling resulted in the development of coarser structure (α+β), while air cooling resulted in much finer structure with widmanstatten morphology of α at the grain boundaries. Quenching from solution annealing temperature formed α’ martensite, their proportion being dependent on the temperature in β phase field. It is well known that the transformation of β to α follows Burger orientation relationship (OR). In order to reconstruct the microstructure of parent β phase, a MATLAB code was written using neighbor-to-neighbor, triplet method and Tari’s method. The code was tested on the annealed samples (1066C solution annealing temperature followed by furnace cooling to room temperature). The parent phase data thus generated was then plotted using the TSL-OIM software. The reconstruction results of the above methods were compared and analyzed. The Tari’s approach (clustering approach) gave better results compared to neighbor-to-neighbor and triplet method but the time taken by the triplet method was least compared to the other two methods.

Keywords: Ti-6Al-4V alloy, microstructure, electron backscattered diffraction, parent phase reconstruction

Procedia PDF Downloads 423

Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

Abstract:

Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

Procedia PDF Downloads 114

Authors: Maatoug Hassine, Mourad Hrizi

Abstract:

In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: geometric inverse source problem, heat equation, topological optimization, topological sensitivity, Kohn-Vogelius formulation

Procedia PDF Downloads 280