Breast Cancer Detection Using a Hybrid Finite Difference Frequency Domain and Particle Swarm Optimization Techniques

Zainud-Deen, S.H.; Hassen, Walaa Mohamed; Ali, Emad El deen; Hassan, Emadeldeen

doi:10.2528/pierb07112703

Cited by 41 publications

(4 citation statements)

References 22 publications

(24 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, a swarm-based reconstruction algorithm for the detection and characterization of multiple inclusions in concrete structures has been presented in [156]. Moreover, a PSO-based technique for early cancer detection has been discussed in [170].…”

Section: Eas-based Approaches For Inverse Scatteringmentioning

confidence: 99%

Evolutionary optimization as applied to inverse scattering problems

Rocca¹,

Benedetti²,

Donelli³

et al. 2009

Inverse Problems

398

218

View full text Add to dashboard Cite

This review is aimed at presenting an overview of evolutionary algorithms (EAs) as applied to the solution of inverse scattering problems. The focus of this work is on the use of different population-based optimization algorithms for the reconstruction of unknown objects embedded in an inaccessible region when illuminated by a set of microwaves. Starting from a general description of the structure of EAs, the classical stochastic operators responsible for the evolution process are described. The extension to hybrid implementations when integrated with local search techniques and the exploitation of the 'domain knowledge', either a priori obtained or collected during the optimization process, are also presented. Some theoretical discussions concerned with the convergence issues and a sensitivity analysis on the parameters influencing the stochastic process are reported as well. Successively, a review on how various researchers have applied or customized different evolutionary approaches to inverse scattering problems is carried out ranging from the shape reconstruction of perfectly conducting objects to the detection of the dielectric properties of unknown scatterers up to applications to sub-surface or biomedical imaging. Finally, open problems and envisaged developments are discussed.

show abstract

Section: Eas-based Approaches For Inverse Scatteringmentioning

confidence: 99%

Evolutionary optimization as applied to inverse scattering problems

Rocca¹,

Benedetti²,

Donelli³

et al. 2009

Inverse Problems

398

218

View full text Add to dashboard Cite

show abstract

“…Several other approaches hybridize PSO with other methods so as to improve the current state of the art of several medical problems. In [369], for instance, a technique using finite-difference frequency domain is hybridized with PSO for reconstructing cell dimension in breast cancer and to find its position using 2-D and 3-D breast models. in [370], a method for segmenting breast tumor images using modified automatic seeded region growing based on PSO-based image clustering is proposed.…”

Section: Applications Of Bio-inspired Optimizationmentioning

confidence: 99%

Bio-inspired computation: Where we stand and what's next

Ser

Osaba

Molina

et al. 2019

Swarm and Evolutionary Computation

481

106

View full text Add to dashboard Cite

show abstract

“…A similar work was carried out in [23,24]. GPU-based implementations of the PSO algorithm for electromagnetic applications were reported earlier in [25,26] for inverse scattering problems and breast cancer research utilizing the finite difference frequency domain method. In [27], the authors investigate the optimization of a simple patch using PSO.…”

Section: Introductionmentioning

confidence: 95%

Bio‐inspired optimization for electromagnetic structure design using full‐wave techniques on GPUs

Kıłıc

El-Araby

Nguyen

et al. 2013

Int J Numerical Modelling

View full text Add to dashboard Cite

The electromagnetic modeling of antennas and radio frequency devices has become increasingly challenging as the applications demand intricate and complex designs, such as fine features embedded in electrically large structures or integrated systems (e.g., antennas on vehicles). Often the design stage is further challenged by the need to find an optimal solution, which results in a numerically intensive problem. The objective of this paper is to investigate the use of graphics processing units (GPUs) in such challenging design and optimizations. Two full-wave approaches (method of moments and rigorous coupled wave analysis) are discussed along with a bio-inspired optimization technique, namely the particle swarm optimization. The inherent parallel nature of the GPUs is utilized in implementing the most numerically intensive parts of these full-wave methods. Furthermore, the independent search mechanism employed by the particle swarm optimization in its agent-based search renders itself to parallelism offered by GPUs. The paper demonstrates the acceleration achieved by the GPUs in designing a variety of radio frequency structures such as reconfigurable patch antennas and antireflective surfaces.

show abstract

Breast Cancer Detection Using a Hybrid Finite Difference Frequency Domain and Particle Swarm Optimization Techniques

Cited by 41 publications

References 22 publications

Evolutionary optimization as applied to inverse scattering problems

Evolutionary optimization as applied to inverse scattering problems

Bio-inspired computation: Where we stand and what's next

Bio‐inspired optimization for electromagnetic structure design using full‐wave techniques on GPUs

Contact Info

Product

Resources

About