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
TL;DR
SAMJ is a user-friendly ImageJ/Fiji plugin that leverages the Segment Anything Model to enable fast, interactive, and real-time image annotation, significantly reducing the labor involved in biomedical image dataset labeling.
Contribution
This paper introduces SAMJ, a novel plugin that integrates SAM into ImageJ/Fiji for efficient, real-time image annotation in biomedical research.
Findings
Enables one-click, interactive annotations.
Accelerates dataset labeling process.
Operates seamlessly on standard computers.
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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Taxonomy
TopicsImage Retrieval and Classification Techniques · Advanced Image and Video Retrieval Techniques · Video Analysis and Summarization