Ultrasound-elastic-image-assisted diagnosis of pulmonary nodules based on genetic algorithm

Autor:	Hua Jing, Wei Feng, Yan Li, Yu-Jie Dong
Rok vydání:	2020
Předmět:	business.industry Computer science Ultrasound ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Pattern recognition Image (mathematics) ComputingMethodologies_PATTERNRECOGNITION Artificial Intelligence Genetic algorithm False positive paradox Point (geometry) Artificial intelligence business Software
Zdroj:	Neural Computing and Applications. 32:18305-18314
ISSN:	1433-3058 0941-0643
Popis:	In the process of ultrasound elastic image detection of pulmonary nodules, due to various factors, the detection process of nodules will produce less sensitive and higher false positives, which will affect the detection accuracy of nodules. In order to improve the ultrasound-assisted diagnosis of pulmonary nodules, this study based on genetic algorithm and combined with fish-following algorithm image recognition technology to construct an improved algorithm based on genetic algorithm. In addition, this study combs and improves the algorithm through process design and sets up the simulation environment for algorithm simulation research. Finally, in order to verify the performance of the algorithm, the ultrasound image of the pulmonary nodule is analyzed by an example to obtain the processed recognition image. From the point of view of identification, the algorithm proposed in this study has certain clinical effects and can provide theoretical reference for subsequent related research.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5d1f6d07112a2e4c309bb4612880bab7 https://doi.org/10.1007/s00521-020-04956-x Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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