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Devisetty, Venkata Sai Deepika (2023) Identification and Detection of Brain Tumors using Machine learning and Deep Learning methods. Masters thesis, Dublin, National College of Ireland.
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Abstract
The challenge of addressing critical ailments such as tumors without manual intervention is substantial. Brain tumors, with their potential to induce cerebral pressure, hemorrhage, and mortality, underscore the gravity of the issue. In this study, we propose a novel approach using machine learning and deep learning techniques for the accurate detection of various brain tumor types. Our methodology encompasses machine learning tools, including SVM and Naive Bayes, as well as deep learning frameworks like CNN, VGG, and Inception. Leveraging a diverse dataset representing different brain tumor scenarios, we rigorously evaluate our models using metrics such as accuracy, precision, recall, and F1-score. This research offers a promising pathway toward enhanced diagnostic automation in the context of brain tumor detection.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Mulwa, Catherine UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RB Pathology Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning Q Science > Life sciences > Medical sciences > Pathology > Tumors |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Tamara Malone |
| Date Deposited: | 08 Nov 2024 14:01 |
| Last Modified: | 08 Nov 2024 14:01 |
| URI: | https://norma.ncirl.ie/id/eprint/7179 |
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