Yucca: A Deep Learning Framework For Medical Image Analysis
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929440339001344 |
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| author | Llambias, Sebastian Nørgaard Machnio, Julia Munk, Asbjørn Ambsdorf, Jakob Nielsen, Mads Ghazi, Mostafa Mehdipour |
| author_facet | Llambias, Sebastian Nørgaard Machnio, Julia Munk, Asbjørn Ambsdorf, Jakob Nielsen, Mads Ghazi, Mostafa Mehdipour |
| contents | Medical image analysis using deep learning frameworks has advanced healthcare by automating complex tasks, but many existing frameworks lack flexibility, modularity, and user-friendliness. To address these challenges, we introduce Yucca, an open-source AI framework available at https://github.com/Sllambias/yucca, designed specifically for medical imaging applications and built on PyTorch and PyTorch Lightning. Yucca features a three-tiered architecture: Functional, Modules, and Pipeline, providing a comprehensive and customizable solution. Evaluated across diverse tasks such as cerebral microbleeds detection, white matter hyperintensity segmentation, and hippocampus segmentation, Yucca achieves state-of-the-art results, demonstrating its robustness and versatility. Yucca offers a powerful, flexible, and user-friendly platform for medical image analysis, inviting community contributions to advance its capabilities and impact. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_19888 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Yucca: A Deep Learning Framework For Medical Image Analysis Llambias, Sebastian Nørgaard Machnio, Julia Munk, Asbjørn Ambsdorf, Jakob Nielsen, Mads Ghazi, Mostafa Mehdipour Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Image and Video Processing Medical image analysis using deep learning frameworks has advanced healthcare by automating complex tasks, but many existing frameworks lack flexibility, modularity, and user-friendliness. To address these challenges, we introduce Yucca, an open-source AI framework available at https://github.com/Sllambias/yucca, designed specifically for medical imaging applications and built on PyTorch and PyTorch Lightning. Yucca features a three-tiered architecture: Functional, Modules, and Pipeline, providing a comprehensive and customizable solution. Evaluated across diverse tasks such as cerebral microbleeds detection, white matter hyperintensity segmentation, and hippocampus segmentation, Yucca achieves state-of-the-art results, demonstrating its robustness and versatility. Yucca offers a powerful, flexible, and user-friendly platform for medical image analysis, inviting community contributions to advance its capabilities and impact. |
| title | Yucca: A Deep Learning Framework For Medical Image Analysis |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Image and Video Processing |
| url | https://arxiv.org/abs/2407.19888 |