Multi-objective Archimedes Optimization Algorithm with Fusion-based Deep Learning model for brain tumor diagnosis and classification

Earlier identification of brain tumors (BT) is essential to increase the survival rate. Magnetic Resonance Imaging (MRI) is a commonly employed method that records brain abnormalities by the use of several modalities for clinical study. The recently developed computer vision and image processing sch...

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Veröffentlicht in:	Multimedia tools and applications Jg. 82; H. 11; S. 16985 - 17007
Hauptverfasser:	Devanathan, B., Kamarasan, M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.05.2023 Springer Nature B.V
Schlagworte:	Abnormalities Algorithms Brain Brain cancer Classification Computer Communication Networks Computer Science Computer vision Data Structures and Information Theory Deep learning Diagnosis Entropy (Information theory) Feature extraction Image contrast Image enhancement Image processing Image segmentation Machine learning Magnetic resonance imaging Medical imaging Multimedia Information Systems Multiple objective analysis Optimization Optimization algorithms Special Purpose and Application-Based Systems Tumors Brain tumor Deep learning Magnetic resonance imaging Multiobjective optimization Fusion models Computer aided diagnosis Image classification
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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