Brain Tumor Detection and Classification Using Deep Learning and Sine-Cosine Fitness Grey Wolf Optimization

Diagnosing a brain tumor takes a long time and relies heavily on the radiologist’s abilities and experience. The amount of data that must be handled has increased dramatically as the number of patients has increased, making old procedures both costly and ineffective. Many researchers investigated a...

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Veröffentlicht in:	Bioengineering (Basel) Jg. 10; H. 1; S. 18
Hauptverfasser:	ZainEldin, Hanaa, Gamel, Samah A., El-Kenawy, El-Sayed M., Alharbi, Amal H., Khafaga, Doaa Sami, Ibrahim, Abdelhameed, Talaat, Fatma M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 22.12.2022 MDPI
Schlagworte:	Algorithms Artificial intelligence Artificial neural networks Bioengineering Brain Brain cancer brain tumor Brain tumors Classification convolutional neural network Deep learning deep learning technique diagnosing Fitness hyperparameters Image classification Machine learning Medical imaging Medical research Neural networks Optimization Training Trigonometric functions Tumors deep learning technique brain tumor hyperparameters optimization convolutional neural network diagnosing
ISSN:	2306-5354, 2306-5354
Online-Zugang:	Volltext
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