Performance optimization of hunger games search for multi-threshold COVID-19 image segmentation

Hao, Shuhui; Huang, Changcheng; Heidari, Ali Asghar; Shao, Qike; Chen, Huiling

doi:10.1007/s11042-023-16116-z

Cited by 3 publications

(2 citation statements)

References 115 publications

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“…Non-Convexity: The objective functions in COVID-19 optimization problems are often nonconvex, meaning they have multiple local optima [48]. Traditional optimization methods can struggle to find the global optimum in such cases, leading to the risk of settling for suboptimal solutions.…”

Section: Other Optimizations Toolsmentioning

confidence: 99%

Global Optimization Theories and Techniques for COVID-19

Wang,

Wen,

2023

Preprint

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As the COVID-19 pandemic has caused enormous damage to society, economy and public health security, it is crucial to combat the epidemic and allocate social and health resources effectively. Global optimization algorithms are extensively used in many domains to find optimal solutions to complex problems. Thus, a survey of three typical global optimizations applied on the COVID-19 pandemic is timely. This article is structured into three typical global optimization algorithms - Genetic Algorithm, Particle Swarm Optimization, and Cat Swarm Optimization - and summarizes the framework models and practical applications, as well as other optimization methods that may be applied to COVID-19. Finally, current unresolved challenges and future research opportunities to be explored are summarized.

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Section: Other Optimizations Toolsmentioning

confidence: 99%

Global Optimization Theories and Techniques for COVID-19

Wang,

Wen,

2023

Preprint

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“…From Equations (10-12), the gur_m shaded section can be used as the foundation of the Ti and Tj level (K), thus allowing ih gihanna (bb (K)) and the dark segment ((_d (K)) [32] to be calculated. Ti and Tj are calculated as follows:…”

Section: B Fuzzy Entropy-based Multi-cancer Thresholdingmentioning

confidence: 99%

Provably Efficient Multi-Cancer Image Segmentation Based on Multi-Class Fuzzy Entropy

Abduljabbar

2023

IJCAI

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One of the segmentation techniques with the greatest degree of success used in numerous recent applications is multi-level thresholding. The selection of appropriate threshold values presents difficulties for traditional methods, however, and, as a result, techniques have been developed to address these difficulties multidimensionally. Such approaches have been shown to be an efficient way of identifying the areas affected in multi-cancer cases in order to define the treatment area. Multi-cancer methods that facilitate a certain degree of competence are thus required. This study tested storing MRI brain scans in a multidimensional image database, which is a significant departure from past studies, as a way to improve the efficacy, efficiency, and sensitivity of cancer detection. The evaluation findings offered success rates for cancer diagnoses of 99.

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