A review of image processing methods for fetal head and brain analysis in ultrasound images

Background and objective: Examination of head shape and brain during the fetal period is paramount to evaluate head growth, predict neurodevelopment, and to diagnose fetal abnormalities. Prenatal ultrasound is the most used imaging modality to perform this evaluation. However, manual interpretation of these images is challenging and thus, image processing methods to aid this task have been proposed in the literature. This article aims to present a review of these state-of-the-art methods. Methods: In this work, it is intended to analyze and categorize the different image processing methods to evaluate fetal head and brain in ultrasound imaging. For that, a total of 109 articles published since 2010 were analyzed. Different applications are covered in this review, namely analysis of head shape and inner structures of the brain, standard clinical planes identification, fetal development analysis, and methods for image processing enhancement. Results: For each application, the reviewed techniques are categorized according to their theoretical approach, and the more suitable image processing methods to accurately analyze the head and brain are identified. Furthermore, future research needs are discussed. Finally, topics whose research is lacking in the literature are outlined, along with new fields of applications. Conclusions: A multitude of image processing methods has been proposed for fetal head and brain analysis. Summarily, techniques from different categories showed their potential to improve clinical practice. Nevertheless, further research must be conducted to potentiate the current methods, especially for 3D imaging analysis and acquisition and for abnormality detection. (c) 2022 Elsevier B.V. All rights reserved.FCT - Fundação para a Ciência e a Tecnologia(UIDB/00319/2020)This work was funded by projects “NORTE-01–0145-FEDER- 0 0 0 059 , NORTE-01-0145-FEDER-024300 and “NORTE-01–0145- FEDER-0 0 0 045 , supported by Northern Portugal Regional Opera- tional Programme (Norte2020), under the Portugal 2020 Partner- ship Agreement, through the European Regional Development Fund (FEDER). It was also funded by national funds, through the FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and by FCT and FCT/MCTES in the scope of the projects UIDB/05549/2020 and UIDP/05549/2020 . The authors also acknowledge support from FCT and the Euro- pean Social Found, through Programa Operacional Capital Humano (POCH), in the scope of the PhD grant SFRH/BD/136670/2018 and SFRH/BD/136721/2018

Localization of Cooperative WSN using Distributed PSO with Optimum References

In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity

Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization

In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoãoManuel R.S. Tavares, Ed.). The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging. In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place. We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf

Updating the Lambda modes of a nuclear power reactor

[EN] Starting from a steady state configuration of a nuclear power reactor some situations arise in which the reactor configuration is perturbed. The Lambda modes are eigenfunctions associated with a given configuration of the reactor, which have successfully been used to describe unstable events in BWRs. To compute several eigenvalues and its corresponding eigenfunctions for a nuclear reactor is quite expensive from the computational point of view. Krylov subspace methods are efficient methods to compute the dominant Lambda modes associated with a given configuration of the reactor, but if the Lambda modes have to be computed for different perturbed configurations of the reactor more efficient methods can be used. In this paper, different methods for the updating Lambda modes problem will be proposed and compared by computing the dominant Lambda modes of different configurations associated with a Boron injection transient in a typical BWR reactor. (C) 2010 Elsevier Ltd. All rights reserved.This work has been partially supported by the Spanish Ministerio de Educacion y Ciencia under projects ENE2008-02669 and MTM2007-64477-AR07, the Generalitat Valenciana under project ACOMP/2009/058, and the Universidad Politecnica de Valencia under project PAID-05-09-4285.González Pintor, S.; Ginestar Peiro, D.; Verdú Martín, GJ. (2011). Updating the Lambda modes of a nuclear power reactor. Mathematical and Computer Modelling. 54(7):1796-1801. https://doi.org/10.1016/j.mcm.2010.12.013S1796180154

Development and application of an optimisation architecture with adaptive swarm algorithm for airfoil aerodynamic design

The research focuses on the aerodynamic design of airfoils for a Multi-Mission Unmanned Aerial Vehicle (MM-UAV). Novel shape design processes using evolutionary algorithms (EA) and a surrogate-based management system are developed to address the identified issues and challenges of solution feasibility and computational efficiency associated with present methods. Feasibility refers to the optimality of the converged solution as a function of the defined objectives and constraints. Computational efficiency is a measure of the number of design iterations needed to achieve convergence to the theoretical optimum. Airfoil design problems are characterised by a multi-modal solution topology. Present gradient-based optimisation methods do not converge to an optimal profile, hence solution feasibility is compromised. Population-based optimisation methods including the Genetic Algorithm (GA) have been used in the literature to address this issue. The GA can achieve solution feasibility, yet it is computationally time-intensive, hence efficiency is compromised. Novel EAs are developed to address the identified shortcomings of present methods. A variant to the original Particle Swarm Optimisation algorithm (PSO) is presented. Novel mutation operators are implemented which facilitate the transition of the search particles toward a global solution. The methodology addresses the limited search performance of the original PSO algorithm for multi-modal problems, while maintaining acceptable computational efficiency for aerodynamic design applications. Demonstration of the developed principles confirmed the merits of the proposed design approach. Airfoil optimisation for a low-speed flight profile achieved drag performance improvement that is lower than a off-the-shelf shape designed for the intent role. Acceptable computational efficiency is achieved by restricting the optimisation phase to promising solution regions through the development of a novel, design variable search space mapping structure. The merit of the optimisation framework is further confirmed by transonic airfoil design for high-speed missions. The wave drag of the established optima is lower than the identified, off-the-shelf benchmark. Concurrently significant computational time-savings are achieved relative to the design methodologies present in the literature. A novel surrogate-assisted optimisation framework by the definition of an Artificial Neural Network with a pattern recognition model is developed to further improve the computational efficiency. This has the potential of enhancing the aerodynamic shape design process. The measure of computational efficiency is critical in the development of an optimisation algorithm. Airfoil design simulations presented required 80\% fewer design iterations to achieve convergence than the GA. Computational time-savings spanning days was achieved by the innovative algorithms developed relative to the GA. Hence, computational efficiency of the developed processes is confirmed. Aircraft shape design simulations involve three-dimensional configurations which require excessive computational effort due to the use of high-fidelity solvers for flow analysis in the optimisation process. It is anticipated that the confirmed computational efficiency performance of the design structure presented on two-dimensional cases will be transferable to three-dimensional shape design problems. It is further expected that the novel principles will be applicable for analysis within a multidisciplinary design structure for the development of a MM-UAV

Optimisation of Microfluidic Flow Systems

This project investigates the fluid flow and heat transfer in microfluidic flow systems using Computational Fluid Dynamics (CFD) and experiments. The first part of this work focuses on developing a CFD - enabled optimisation methodology of the geometrical features of i) a microfluidic heatsink design and ii) a single-phase (SP) continuous-flow (CF) Polymerase Chain Reaction (PCR) Device. This is achieved using COMSOL Multiphysics 5.4 ®to simulate the fluid flow, heat transfer (and PCR kinetics for the case of the microfluidic PCR device). Optimisation problems are then formed, selecting objective functions related to the performance of the devices. Design of Experiments is then used together with COMSOL Multiphysics 5.4 ® to collect the values of the objective functions over the design domain. Matlab© is then used to generate the response surfaces of the objective functions, using different techniques, locate the optimum design solutions (genetic algorithm, multi-level coordinate search method) and obtain the Pareto front for the cases of multi-objective optimisation problems. Results of this work indicate the possibility of significantly enhancing the performance of SP-CF-PCR devices in terms of the DNA amplification, device volume, total operating time and total pressure drop by up to 16.4%, 43.2%, 17.8% and 80.5% respectively, after applying the appropriate design modifications for each objective. The increase in the DNA amplification is achieved by increasing the channel width and residence times while minimising the channel height. The reduction in the device volume, total operating time and total pressure drop are achieved when using the smallest residence times and higher channel width. According to this investigation, the DNA amplification appears to be linked to the temperature uniformity and to the residence time in the extension zone. The second part of this work focuses on i) obtaining a better understanding of the role that the concentration and presence of droplets play in conjugate heat transfer phenomena in droplet-laden flows, ii) creating and optimising a reusable, cheap and easy-to-fabricate device that can perform Melting Curve Analysis (MCA), in order to facilitate the work of a group of biologists at the University of Leeds. More specifically, this device aims to check for the presence of rare DNA species and possible contaminations in their collected samples in a fast, robust and cheap way, by testing if the DNA product has a unique melting temperature. The experimental setup is designed after performing a series of simulations using COMSOL Multiphysics 5.4 ®, considering different potential designs while at the same time simulating the energy requirements of the system. After finalising the design, a PID temperature controller is implemented on the Arduino Platform, achieving the required temperature difference between the two ends of the device. The results obtained during the experiments demonstrate a successful temperature control that is robust and does not require the adjustment of the PID parameters for the performance of similar experiments in the different temperature ranges tested