Chan, Hoong Kai (2023) Computer Vision in Identifying Brain Tumours with Neural Networks. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.
Full text not available from this repository.Abstract
The process of identifying cancer can be tedious and is prone to inaccuracy, due to lack of experience or skill for the healthcare provider. However, with recent advancements in Artificial Intelligence. It is suggested that machine learning can be implemented to come up with models that are able to accurately identify and classify brain tumours, saving up time, so that a biopsy can be done sooner. The model can be deployed to a web-based application so that the healthcare providers can access it easily and it does not cost anything to do so. Naturally, the target market of this application is mainly doctors and related healthcare professionals, where they will greatly benefit from this solution. In the long run, it is probable that machine learning can be improved much further to identify not only tumours, but other anomalies as well, and perhaps become the norm in the healthcare industry as well. With this project, a CNN brain tumour classification model has been developed and deployed onto the web. Within this system, there are 2 major components which would be the modelling part, where the training and processing is done, and also the Flask framework component where it is deployed on Heroku. To understand more in-depth about the types of Neural Networks, countless hours of research within this field has been identified and studied and also discussed. Both functional and non-functional requirements are discovered thanks to the knowledge gained from the research. Implementation of and evaluation has also been performed to show the performance and also the effectiveness of this proposed system.
| Item Type: | Final Year Project |
|---|---|
| Subjects: | Science > Computer Science |
| Faculties: | Faculty of Computing and Information Technology > Bachelor of Computer Science (Honours) in Data Science |
| Depositing User: | Library Staff |
| Date Deposited: | 21 Aug 2023 06:38 |
| Last Modified: | 21 Aug 2023 06:38 |
| URI: | https://eprints.tarc.edu.my/id/eprint/26063 |
