Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography
This work proposes the use of a Generative Adversarial Network (GAN) to perform data augmentation with the goal of improving image reconstruction in Optoacustic Tomography (OAT) applications. We employ the FastGAN model, a compact net capable of generating high resolution images from small datasets....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universidad de Buenos Aires
2023-12-01
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| Series: | Revista Elektrón |
| Subjects: | |
| Online Access: | http://elektron.fi.uba.ar/index.php/elektron/article/view/185 |
| _version_ | 1797389060386324480 |
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| author | Alejandro Scopa Lopina Martín Germán González Matías Vera |
| author_facet | Alejandro Scopa Lopina Martín Germán González Matías Vera |
| author_sort | Alejandro Scopa Lopina |
| collection | DOAJ |
| description | This work proposes the use of a Generative Adversarial Network (GAN) to perform data augmentation with the goal of improving image reconstruction in Optoacustic Tomography (OAT) applications. We employ the FastGAN model, a compact net capable of generating high resolution images from small datasets. The quality of the generated data was assessed by two methods. First, the Fréchet distance (FID) was measured, observing a decreasing trend throughout the entire GAN training. Then, a U-Net neural network designed for a OAT system with and without augmented data was trained. In this case, the model trained with the extra data generated by the GAN achieved an appreciable improvement in the figures of merit associated with the reconstruction. |
| first_indexed | 2024-03-08T22:50:20Z |
| format | Article |
| id | doaj.art-1d5f56d3be5042e58bb3165e98bbdd38 |
| institution | Directory Open Access Journal |
| issn | 2525-0159 |
| language | English |
| last_indexed | 2024-03-08T22:50:20Z |
| publishDate | 2023-12-01 |
| publisher | Universidad de Buenos Aires |
| record_format | Article |
| series | Revista Elektrón |
| spelling | doaj.art-1d5f56d3be5042e58bb3165e98bbdd382023-12-16T16:14:24ZengUniversidad de Buenos AiresRevista Elektrón2525-01592023-12-0172617010.37537/rev.elektron.7.2.185.2023109Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic TomographyAlejandro Scopa Lopina0Martín Germán González1Matías Vera2Universidad de Buenos AiresFIUBAFIUBAThis work proposes the use of a Generative Adversarial Network (GAN) to perform data augmentation with the goal of improving image reconstruction in Optoacustic Tomography (OAT) applications. We employ the FastGAN model, a compact net capable of generating high resolution images from small datasets. The quality of the generated data was assessed by two methods. First, the Fréchet distance (FID) was measured, observing a decreasing trend throughout the entire GAN training. Then, a U-Net neural network designed for a OAT system with and without augmented data was trained. In this case, the model trained with the extra data generated by the GAN achieved an appreciable improvement in the figures of merit associated with the reconstruction.http://elektron.fi.uba.ar/index.php/elektron/article/view/185tomografía optoacústicaaprendizaje profundoredes generativas de confrontacióndatos sintéticos |
| spellingShingle | Alejandro Scopa Lopina Martín Germán González Matías Vera Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography Revista Elektrón tomografía optoacústica aprendizaje profundo redes generativas de confrontación datos sintéticos |
| title | Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography |
| title_full | Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography |
| title_fullStr | Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography |
| title_full_unstemmed | Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography |
| title_short | Study of Generative Adversarial Networks for Generating Synthetic Data and its Application on Optoacoustic Tomography |
| title_sort | study of generative adversarial networks for generating synthetic data and its application on optoacoustic tomography |
| topic | tomografía optoacústica aprendizaje profundo redes generativas de confrontación datos sintéticos |
| url | http://elektron.fi.uba.ar/index.php/elektron/article/view/185 |
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