An efficient multi-objective memetic genetic algorithm for medical image handling and health safety to support systems in medical internet of things
[ X ]
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Amer Scientific Publishers
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Over the most recent couple of decades, the Evolutionary Algorithms (EA) have been considered as a typical dynamic research zone in the field of medicinal picture preparing and wellbeing administrations. This is a direct result of the presence of numerous streamlining issues in this field which can be comprehended utilizing developmental calculations. Besides, numerous certifiable streamlining issues in the restorative picture handling and wellbeing administrations have more than one target work, and for the most part the issue goals are in struggle with one another. The traditional multi-objective transformative calculations perform well when the streamlining issue has less than three goal functions, where the execution of these calculations altogether degrades when the improvement issue has high number of destinations. To deal with this issue, there is a requirement for growing new versatile transformative streamlining mechanisms which can handle the high target capacities in the medicinal picture preparing and wellbeing administrations advancement issues. In this paper, we propose a new developmental calculation dependent on the NSGA-II calculation to productively take care of the many-target enhancement issues. The proposed calculation adds three plans to improve the capacity of NSGA-II calculation when managing with high objective dimensional streamlining issues. Another productive arranging strategy, savvy file and straightforward nearby pursuit are utilized to accelerate the solutions combination procedure to the POF and upgrade the decent variety of the arrangements. The proposed calculation is contrasted and the cutting edge multi-target advancement calculations utilizing five DTLZ test issues. The outcomes demonstrate that our proposed calculation essentially beats alternate calculations when the quantity of target capacities is high. Moreover, we applied our proposed algorithm on medical imaging health problem which is the melanoma recognition problem to enhance the early detection of melanoma disease.
Açıklama
Anahtar Kelimeler
Many-Objective Optimization Problems, NSGA-II, Multi-Objective Problems, Health Safety Services, Medical Image Handling, Evolutionary Algorithms
Kaynak
Journal of Medical Imaging and Health Informatics
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
10
Sayı
1
