A comparative analysis of deep learning models for lung segmentation on X-ray images
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866929488978247680 |
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| author | Hryniewska-Guzik, Weronika Bilski, Jakub Chrostowski, Bartosz Sbahi, Jakub Drak Biecek, Przemysław |
| author_facet | Hryniewska-Guzik, Weronika Bilski, Jakub Chrostowski, Bartosz Sbahi, Jakub Drak Biecek, Przemysław |
| contents | Robust and highly accurate lung segmentation in X-rays is crucial in medical imaging. This study evaluates deep learning solutions for this task, ranking existing methods and analyzing their performance under diverse image modifications. Out of 61 analyzed papers, only nine offered implementation or pre-trained models, enabling assessment of three prominent methods: Lung VAE, TransResUNet, and CE-Net. The analysis revealed that CE-Net performs best, demonstrating the highest values in dice similarity coefficient and intersection over union metric. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_06455 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A comparative analysis of deep learning models for lung segmentation on X-ray images Hryniewska-Guzik, Weronika Bilski, Jakub Chrostowski, Bartosz Sbahi, Jakub Drak Biecek, Przemysław Image and Video Processing Computer Vision and Pattern Recognition Machine Learning Robust and highly accurate lung segmentation in X-rays is crucial in medical imaging. This study evaluates deep learning solutions for this task, ranking existing methods and analyzing their performance under diverse image modifications. Out of 61 analyzed papers, only nine offered implementation or pre-trained models, enabling assessment of three prominent methods: Lung VAE, TransResUNet, and CE-Net. The analysis revealed that CE-Net performs best, demonstrating the highest values in dice similarity coefficient and intersection over union metric. |
| title | A comparative analysis of deep learning models for lung segmentation on X-ray images |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2404.06455 |