Brain Tumor Analysis Using Deep Learning and VGG-16 Ensembling Learning Approaches
Tianjin University · Mbeya University of Science and Technology
Abstract
A brain tumor is a distorted tissue wherein cells replicate rapidly and indefinitely, with no control over tumor growth. Deep learning has been argued to have the potential to overcome the challenges associated with detecting and intervening in brain tumors. It is well established that the segmentation method can be used to remove abnormal tumor regions from the brain, as this is one of the advanced technological classification and detection tools. In the case of brain tumors, early disease detection can be achieved effectively using reliable advanced A.I. and Neural Network classification algorithms. This study aimed to critically analyze the proposed literature solutions, use the Visual Geometry Group (VGG…
Citation impact
- FWCI
- 21.32
- Percentile
- 100%
- References
- 61
Authors
5Topics & keywords
- Convolutional neural network
- Computer science
- Artificial intelligence
- Brain tumor
- Deep learning
- Segmentation
- Pattern recognition (psychology)
- Brain disease