Artificial intelligence processing for enhancing an intelligent sensor - II
This final year project focused on the objective of finding an Artificial Intelligence algorithm for reconstructing photoacoustic images. The theory behind the algorithms used, their implementation and results were discussed. First, the significance of this project was explained through the need...
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| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/167049 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | This final year project focused on the objective of finding an Artificial Intelligence
algorithm for reconstructing photoacoustic images. The theory behind the algorithms
used, their implementation and results were discussed.
First, the significance of this project was explained through the need for a
non-invasive blood pressure measurement technique such as Photoacoustic Imaging.
The working principle of a Photoacoustic Microscopy System was explained along
with the conversion of the signals to images.
The enhancement of the image details using convolutional neural networks like
U-Net and Generative Adversarial Network was introduced. The network
architectures and the advantages were highlighted.
The two networks were constructed, and an input dataset of 1000 preprocessed
photoacoustic images was used. The models built were evaluated based on the test
dataset using metrics such as Peak signal-to-noise ratio and Structural Similarity
Index Measure. The output of the models that are the reconstructed images are also
compared. The best reconstruction algorithm was proposed based on the results
obtained. |
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