Mentors: Dimiter Prodanov <dimiterpp@gmail.com>, Teodor Minev <teodorminev98@gmail.com>
Skill level: Intermediate
Required skills: Java
Time commitment: Full time or part time (150 hours)
About: The Active Segmentation platform for ImageJ (ASP/IJ) [2] was developed in the scope of GSOC 2016 - 2024. The plugin provides a general-purpose environment that allows biologists and other domain experts to use transparently state-of-the-art techniques in machine learning to achieve excellent image segmentation and classification. ImageJ [1] is a public-domain Java image processing program extensively used in life and material sciences. The program was designed with an open architecture and is extensible via plugins.
Aims: The project will streamline and simplify the existing UI implementation using WindowBuilder for Eclipse [3]:
- Fix existing issues and bugs
- UI implementation and testing Minimal set of deliverables
- Requirement specification - Prepared by the candidate after understanding the functionality
- System Design - Detailed plan for development of the plugin and test cases.
- Implementation and testing - Details of implementation and testing of the platform
Website/references:
- ImageJ: https://imagej.nih.gov/
- Active Segmentation: GitHub - sumit3203/ACTIVESEGMENTATION: Active Segmentation Project
- Eclipse IDE https://www.eclipse.org/
Tech keywords: Java, ImageJ, Active Segmentation