University of Twente Student Theses
Photoacoustic Image Reconstruction using Continuous Neural Representations
A.B., A.B. (2025) Photoacoustic Image Reconstruction using Continuous Neural Representations.
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| Abstract: | Photoacoustic imaging techniques are capable of creating high-resolution images with high optical contrast. It has the potential to be used for breast cancer screening, but there are still some hurdles to overcome. One of them is the need for faster reconstruction algorithms, which is the main topic of this thesis. Reconstructing photoacoustic images over large fields of view is computationally expensive, not just because of the large domains involved, but also because the measurements can be sparse, requiring many iterations of an iterative algorithm. In this thesis, several deep learning techniques, known as continuous neural representations, are explored to see whether they can speed up photoacoustic reconstruction and improve the reconstruction quality by providing a continuous view of the underlying objects. |
| Item Type: | Essay (Master) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 31 mathematics, 33 physics, 50 technical science in general |
| Programme: | Applied Mathematics MSc (60348) |
| Link to this item: | https://purl.utwente.nl/essays/106288 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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