Brain Tumor Detection and Classification Using a Hyperparameter Tuned Convolutional Neural Network
- Title
- Brain Tumor Detection and Classification Using a Hyperparameter Tuned Convolutional Neural Network
- Creator
- Banerjee A.; Jaiswal K.; Biswas T.; Sharma V.; Bal M.; Mishra S.
- Description
- Brain tumor detection using MRI scans when integrated with a deep learning approach can be immensely applied in identifying the tumor at early stages, with minimum medical professional aid. This research paper aims to develop an advanced predictive model that accurately classify brain tumors as benign or malignant using MRI scans. Here, a novel convolutional neural network (CNN) model is proposed to automate tumor detection and improve diagnosis accuracy. The model used a dataset of around 7000 brain cancer data classified into 4 labels which include glioma, meningioma, pituitary, and no tumor. Data wrangling and pre-processing are then applied to unify the images into a single format and remove any inconsistencies. Further the records are segregated into train and test samples with a 70-30 split. The proposed model recorded an optimum accuracy of 94.82%, precision of 94.2%, recall value of 93.7% and f-score metric of 93.9% respectively. In conclusion, the paper concluded that the proposed model can be applied to enhance the precision of both brain tumor diagnosis and prognosis. 2023 IEEE.
- Source
- Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023, pp. 502-506.
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Brain Tumor detection; Convolutional neural network; Data pre-processing; MRI scans; Prediction
- Coverage
- Banerjee A., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Jaiswal K., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Biswas T., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Sharma V., CHRIST (Deemed to Be University, Computer Science Department, Delhi NCR, India; Bal M., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Mishra S., Kalinga Institute of Industrial Technology, Deemed to Be University, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835030448-0
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Banerjee A.; Jaiswal K.; Biswas T.; Sharma V.; Bal M.; Mishra S., “Brain Tumor Detection and Classification Using a Hyperparameter Tuned Convolutional Neural Network,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19725.