Lai, Khin Wee and Shoaib, Muhammad Ali and Chuah, Joon Huang and Nizar, Muhammad Hanif Ahmad and Anis, Shazia and Ching, Serena Low Woan (2021) Detection of aortic valve using deep learning approaches. In: 2020 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2020, 1 - 3 March 2021, Virtual, Langkawi Island.
Full text not available from this repository.Abstract
Detection of the aortic valve is one of the critical processes in the diagnosis of cardiovascular diseases. Automatic detection of the aortic valve can assist in improving the diagnostic precision and can further be used for different medical studies like image registration and segmentation. The manual detection of the aortic valve is time-consuming and labor-intensive. The machine learning method is utilized for the automatic detection of the aortic valve in this preliminary study. AlexNet convolutional neural network architecture is used due to its high accuracy for the desired purpose. The trained model was tested on a patient dataset of 120 andthe method was found to be able to detectthe aortic valve 95% accurately.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | None |
| Uncontrolled Keywords: | Aortic valve; Deep learning; Detection |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Engineering > Biomedical Engineering Department |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 17 Oct 2023 08:17 |
| Last Modified: | 17 Oct 2023 08:17 |
| URI: | http://eprints.um.edu.my/id/eprint/35404 |
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