Binary tunicate swarm algorithm based novel feature selection framework for mammographic mass classification

The efficacy of a CAD system for mammographic mass classification depends on high-quality features for maximum throughput. Feature selection is crucial for accurate breast cancer diagnosis in CAD solutions. Leveraging the success of metaheuristics, a novel binary tunicate swarm algorithm is proposed...

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Veröffentlicht in:	Measurement : journal of the International Measurement Confederation Jg. 235; S. 114928
Hauptverfasser:	Laishram, Romesh, Rabidas, Rinku
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.08.2024
Schlagworte:	Binary tunicate swarm algorithm CAD system Feature selection Mammographic mass categorization Feature selection Binary tunicate swarm algorithm Mammographic mass categorization CAD system
ISSN:	0263-2241
Online-Zugang:	Volltext
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