INCF’s Active Segmentation for ImageJ working group – including GSOC students – has just published a paper in Brain Sciences as part of a special issue on neuroinformatics and signal processing.  Congratulations to mentors Dimiter Prodanov & Sumit Vohra, and GSOC students Mukesh Gupta, Sanjeev Dubay, Joanna Stachera, Raghavendra Singh Chauhan, & Piyumal Demotte!

The Active Segmentation platform is an ImageJ plugin that integrates expert domain knowledge, providing partial ground truth, with geometrical feature extraction based on multi-scale signal processing combined with machine learning. The filtering functionality of the platform is extendable via plugins, and the built-in filters can also be used in stand-alone mode.

The platform supports rich and extensible metadata to ensure reproducibility of the classification and segmentation results across sessions. This design choice is made specifically to ensure support of the Findability, Accessibility, Interoperability, and Reusability (FAIR) data management principles. All filtering settings are stored in the project file in JavaScript Object Notation (JSON) format.

Learn more about it here: bit.ly/INCFwgActiveSegblog

Read the paper here: bit.ly/ActiveSegmentationpaper