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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.02783 |
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| _version_ | 1866909635000139776 |
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| author | Garcia-Lopez-de-Haro, Carlos Fuster-Barcelo, Caterina Rueden, Curtis T. Heras, Jonathan Ulman, Vladimir Franco-Barranco, Daniel Ines, Adrian Eliceiri, Kevin W. Olivo-Marin, Jean-Christophe Tinevez, Jean-Yves Sage, Daniel Munoz-Barrutia, Arrate |
| author_facet | Garcia-Lopez-de-Haro, Carlos Fuster-Barcelo, Caterina Rueden, Curtis T. Heras, Jonathan Ulman, Vladimir Franco-Barranco, Daniel Ines, Adrian Eliceiri, Kevin W. Olivo-Marin, Jean-Christophe Tinevez, Jean-Yves Sage, Daniel Munoz-Barrutia, Arrate |
| contents | Mask annotation remains a significant bottleneck in AI-driven biomedical image analysis due to its labor-intensive nature. To address this challenge, we introduce SAMJ, a user-friendly ImageJ/Fiji plugin leveraging the Segment Anything Model (SAM). SAMJ enables seamless, interactive annotations with one-click installation on standard computers. Designed for real-time object delineation in large scientific images, SAMJ is an easy-to-use solution that simplifies and accelerates the creation of labeled image datasets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_02783 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model Garcia-Lopez-de-Haro, Carlos Fuster-Barcelo, Caterina Rueden, Curtis T. Heras, Jonathan Ulman, Vladimir Franco-Barranco, Daniel Ines, Adrian Eliceiri, Kevin W. Olivo-Marin, Jean-Christophe Tinevez, Jean-Yves Sage, Daniel Munoz-Barrutia, Arrate Computer Vision and Pattern Recognition Mask annotation remains a significant bottleneck in AI-driven biomedical image analysis due to its labor-intensive nature. To address this challenge, we introduce SAMJ, a user-friendly ImageJ/Fiji plugin leveraging the Segment Anything Model (SAM). SAMJ enables seamless, interactive annotations with one-click installation on standard computers. Designed for real-time object delineation in large scientific images, SAMJ is an easy-to-use solution that simplifies and accelerates the creation of labeled image datasets. |
| title | SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.02783 |