Multi-Classification of Brain Tumor Images Using Deep Neural Network
Indexed incrossrefdoaj
Abstract
Brain tumor classification is a crucial task to evaluate the tumors and make a treatment decision according to their classes. There are many imaging techniques used to detect brain tumors. However, MRI is commonly used due to its superior image quality and the fact of relying on no ionizing radiation. Deep learning (DL) is a subfield of machine learning and recently showed a remarkable performance, especially in classification and segmentation problems. In this paper, a DL model based on a convolutional neural network is proposed to classify different brain tumor types using two publicly available datasets. The former one classifies tumors into (meningioma, glioma, and pituitary tumor). The other one…
Citation impact
733
total citations
- FWCI
- 29.74
- Percentile
- 100%
- References
- 44
Citations per year
Authors
3Topics & keywords
Topics
Keywords
- Computer science
- Artificial neural network
- Artificial intelligence
- Pattern recognition (psychology)
- Contextual image classification
- Brain tumor
- Image (mathematics)
- Medicine
UN Sustainable Development Goals
- Good health and well-being
No related works found for this paper.