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

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arxiv 2506.02783 v1 pith:IWMK4N5H submitted 2025-06-03 cs.CV

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
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Jean-Christophe Olivo-Marin Jean-Yves Tinevez Daniel Sage Arrate Munoz-Barrutia
This is my paper
classification cs.CV
keywords samjimageannotationanythingfijiimagejmodelsegment
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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