Brain Tumor Detectin Using Deep Learning Model
- Title
- Brain Tumor Detectin Using Deep Learning Model
- Creator
- Menachery J.; Anand I.K.; Thiruthuvanathan M.M.
- Description
- Brain tumor is a life-threatening disease that can disrupt normal brain functioning and have a significant impact on a patient's quality of life. Early detection and diagnosis are crucial for effective treatment. In recent years, deep learning techniques for image analysis and detection have played a vital role in the medical field, supplying more accurate and reliable results. Segmentation, the process of distinguishing between normal and abnormal brain cells or tissues, is a critical step in the detection of brain tumors. In this research, we aim to investigate various techniques for brain tumor detection and segmentation using Magnetic Resonance Imaging (MRI) images. The detection process begins by analyzing the symmetric and asymmetric shape of the brain to identify abnormalities. We will then classify the cells as either Tumored or non-Tumored. This research is aimed at finding a more accurate and efficient method for detecting brain tumors. Four Keras models are compared side by side to find out the best deep learning model for providing a suitable outcome. The models are ResNet50, DenseNet201, Inception V3 and MobileNet. These models gave training accuracy of 85.30%, 78%, 78%, and 77.12% respectively. 2023 IEEE.
- Source
- Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Brain-Tumor detection; Deep Leaning; DenseNet201; Inception V3; MobileNet; ResNet50
- Coverage
- Menachery J., Christ (Deemed to Be University), Department of Computer Science, Karnataka, Bengaluru, India; Anand I.K., Christ (Deemed to Be University), Department of Computer Science, Karnataka, Bengaluru, India; Thiruthuvanathan M.M., Christ (Deemed to Be University), Department of Computer Science, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835033577-4
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Menachery J.; Anand I.K.; Thiruthuvanathan M.M., “Brain Tumor Detectin Using Deep Learning Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 26, 2025, https://archives.christuniversity.in/items/show/19794.