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arXiv · 2506.02783

SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model

Carlos Garcia-Lopez-de-Haro·Caterina Fuster-Barcelo·Curtis T. Rueden·Jonathan Heras·Vladimir Ulman·Daniel Franco-Barranco·Adrian Ines·Kevin W. Eliceiri·Jean-Christophe Olivo-Marin·Jean-Yves Tinevez·Daniel Sage·Arrate Munoz-Barrutia
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Abstract

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.

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Carlos Garcia-Lopez-de-Haro, Caterina Fuster-Barcelo, Curtis T. Rueden, Jonathan Heras, Vladimir Ulman, Daniel Franco-Barranco, Adrian Ines, Kevin W. Eliceiri, Jean-Christophe Olivo-Marin, Jean-Yves Tinevez, Daniel Sage, Arrate Munoz-Barrutia. 2025-06-03. SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model. https://arxiv.org/abs/2506.02783

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