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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Potipireddi Sai Pratyusha
مؤلفون آخرون: Zheng Yuanjin
التنسيق: Final Year Project
اللغة:English
منشور في: Nanyang Technological University 2023
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/167049
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص: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.