Improved brain tumor classification through DenseNet121 based transfer learning

Brain tumors have a big effect on a person’s health by letting abnormal cells grow unchecked in the brain. This means that early and correct diagnosis is very important for effective treatment. Many of the current diagnostic methods are time-consuming, rely primarily on hand interpretation, and freq...

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Veröffentlicht in:	Discover. Oncology Jg. 16; H. 1; S. 1645 - 23
Hauptverfasser:	Rasheed, Mehwish, Jaffar, Muhammad Arfan, Akram, Arslan, Rashid, Javed, Alshalali, Tagrid Abdullah N., Irshad, Asma, Sarwar, Nadeem
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 27.08.2025 Springer Nature B.V Springer
Schlagworte:	Accuracy Algorithms Automation Brain cancer Brain research Cancer Research Classification Datasets Deep learning DenseNet121 Glioma Illnesses Internal Medicine Literature reviews Machine learning Magnetic resonance imaging Medical imaging Medicine Medicine & Public Health Molecular Medicine Multiclass brain tumor classification Oncology Radiotherapy Support vector machines Surgical Oncology Transfer learning Tumors Deep learning Transfer learning Multiclass brain tumor classification DenseNet121
ISSN:	2730-6011, 2730-6011
Online-Zugang:	Volltext
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