Speaker
Description
The SAMJ Annotator is a new plugin for ImageJ, Fiji, and Icy that offers user-friendly access to advanced image-segmentation models. These transformer-based models, including the Segment Anything Model (SAM) variants, have shown exceptional performance in segmenting complex and heterogeneous objects in natural images.
With SAMJ Annotator, users can easily annotate objects using manual prompts within Fiji. The tool leverages these sophisticated models to ensure accurate contours and efficient segmentation. We have integrated highly efficient SAM models to enable real-time annotation without requiring a GPU. The installation of the SAM environment in Python is fully automated through JDLL, and execution is optimized using shared memory techniques between Python and Java, facilitated by Appose.
In our workshop, we will demonstrate how SAMJ Annotator can be utilized in a scientific context to accelerate the annotation of large 2D microscopy images. This tool is particularly valuable for creating labeled images for training datasets. We will cover seamless installation, model selection, and best practices for annotation. Additionally, we will discuss the appropriate applications of SAMJ, focusing on managing the annotation process for various types of microscopy data. Attendees will gain hands-on experience and learn to use powerful annotation tools to design efficient image-analysis workflows.
| Target audience | Beginner users, Intermediate users, Advanced users, Beginner developers, Intermediate developers, Advanced developers |
|---|---|
| Keywords | fiji, imagej, annotation, SAM, java, microscopy |
