Brain Tumor Detection Based on Deep Learning Approaches and Magnetic Resonance Imaging
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Abstract
The rapid development of abnormal brain cells that characterizes a brain tumor is a major health risk for adults since it can cause severe impairment of organ function and even death. These tumors come in a wide variety of sizes, textures, and locations. When trying to locate cancerous tumors, magnetic resonance imaging (MRI) is a crucial tool. However, detecting brain tumors manually is a difficult and time-consuming activity that might lead to inaccuracies. In order to solve this, we provide a refined You Only Look Once version 7 (YOLOv7) model for the accurate detection of meningioma, glioma, and pituitary gland tumors within an improved detection of brain tumors system. The visual representation of the MRI…
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Topics
Keywords
- Magnetic resonance imaging
- Deep learning
- Neuroimaging
- Artificial intelligence
- Computer science
- Nuclear magnetic resonance
- Neuroscience
- Medicine
UN Sustainable Development Goals
- Industry, innovation and infrastructure
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