Optimized control for medical image segmentation: improved multi-agent systems agreements using Particle Swarm Optimization

Allioui, Hanane; Sadgal, Mohammed; Elfazziki, Aziz

doi:10.1007/s12652-020-02682-9

Cited by 18 publications

(11 citation statements)

References 57 publications

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“…e biggest difference between the newly established "ruxiaogao" and other existing snack food brands lies in the brand background of Funing big cake. In order to highlight the younger market goal of the brand and the category of snack food, it is suggested to adopt the method of category positioning in advance, locate ruxiaogao as "young snack," and publicize it with the advertising slogan of "not snack, but small cake" [20], as shown in Figure 14.…”

Section: Brand Precision Marketing Improvement Strategymentioning

confidence: 99%

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Xue

2022

Mobile Information Systems

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In order to deeply study the macroenvironment, current situation, and the core elements affecting the operation of the product brand system, this paper further improves the product brand communication system from the perspective of precision marketing. Taking JR company’s big cake products as the research object, this study proposes an accurate positioning optimization algorithm based on particle swarm optimization algorithm. Through the experiment of increasing the number of nodes of different algorithms, it is found that the average positioning error will decrease with the increase of the number of nodes under different algorithms. Compared with WSSPCO positioning algorithm, the average error of PSO positioning algorithm is reduced by about 30% due to the number of nodes, and the impact of node density on positioning accuracy is also reduced by about 40%. This algorithm can better achieve accurate positioning. Therefore, it is concluded that product brand communication based on precision marketing should pay attention to accurate positioning, further integrate brand communication channels, and build personalized communication channels.

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Section: Brand Precision Marketing Improvement Strategymentioning

confidence: 99%

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Xue

2022

Mobile Information Systems

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“…We aimed to prove if our proposed QWPSO algorithm had better adaptability for object region shape, operational efficiency, and segmentation accuracy than QPSO and other typical competing reference methods. Test 3 is specifically for demonstrating the advantage of the proposed QWPSO method, the compared tests were implemented in 10 studies listed in references ( 8 , 68 – 77 ), of which publication years were from 2018 to 2021.…”

Section: Resultsmentioning

confidence: 99%

“…To demonstrate the advantage of the proposed QWPSO method, test 3 implements a comparison between ten studies listed from ( 8 , 68 – 77 ) in references whose publication years were from 2018 to 2021. Table 5 shows the original image, reference segmentation results, suggested QWPSO method, and ground truth in the 1st to 4th columns.…”

Section: Resultsmentioning

confidence: 99%

“…Table 6 demonstrates the reference studies ( 8 , 68 – 71 ) published from 2021 to 2020. These studies used newly proposed methods within two years of the methods' publication in higher-level international journals from 2018 to 2019.…”

Section: Resultsmentioning

confidence: 99%

“…Table 7 includes references ( 72 – 77 ) published from 2019 to 2018. In Table 6 , for example, the first row P of Allioui et al ( 68 ) is 0.9176, and the value of 0.9785 is the P results of our proposed QWPSO method. The corresponding segmentation results in rows P, R, and F show that our proposed methods are higher than their reference studies.…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

A Brain Tumor Image Segmentation Method Based on Quantum Entanglement and Wormhole Behaved Particle Swarm Optimization

Zhang

Xue

et al. 2022

Front. Med.

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PurposeAlthough classical techniques for image segmentation may work well for some images, they may perform poorly or not work at all for others. It often depends on the properties of the particular image segmentation task under study. The reliable segmentation of brain tumors in medical images represents a particularly challenging and essential task. For example, some brain tumors may exhibit complex so-called “bottle-neck” shapes which are essentially circles with long indistinct tapering tails, known as a “dual tail.” Such challenging conditions may not be readily segmented, particularly in the extended tail region or around the so-called “bottle-neck” area. In those cases, existing image segmentation techniques often fail to work well.MethodsExisting research on image segmentation using wormhole and entangle theory is first analyzed. Next, a random positioning search method that uses a quantum-behaved particle swarm optimization (QPSO) approach is improved by using a hyperbolic wormhole path measure for seeding and linking particles. Finally, our novel quantum and wormhole-behaved particle swarm optimization (QWPSO) is proposed.ResultsExperimental results show that our QWPSO algorithm can better cluster complex “dual tail” regions into groupings with greater adaptability than conventional QPSO. Experimental work also improves operational efficiency and segmentation accuracy compared with current competing reference methods.ConclusionOur QWPSO method appears extremely promising for isolating smeared/indistinct regions of complex shape typical of medical image segmentation tasks. The technique is especially advantageous for segmentation in the so-called “bottle-neck” and “dual tail”-shaped regions appearing in brain tumor images.

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Integration of Machine Learning and Optimization Techniques for Cardiac Health Recognition

Houssein

Ibrahim²,

Hassaballah

et al. 2022

Studies in Computational Intelligence

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Optimized control for medical image segmentation: improved multi-agent systems agreements using Particle Swarm Optimization

Cited by 18 publications

References 57 publications

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

Precision Marketing and Brand Communication Model Using Particle Swarm Optimization Algorithm

A Brain Tumor Image Segmentation Method Based on Quantum Entanglement and Wormhole Behaved Particle Swarm Optimization

Integration of Machine Learning and Optimization Techniques for Cardiac Health Recognition

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