Cell segmentation with Deep Learning based StarDist 3D

Description:

• I am working on a deep learning-based Stardist 3D model to segment individual cells. To facilitate this, I developed a GUI using PyQt to manually label each cell with its corresponding name, enabling the preparation of high-quality training data.
• The GUI includes several features:Data Loading: It supports loading two volumes (raw and segmented) along with a text file containing class IDs and their corresponding names. The text file can be edited or modified as needed, and the GUI automatically updates the cell IDs and names upon loading.
• Zoom and Transparency: Users can zoom in and out for detailed cell examination and adjust the transparency level between the raw and segmented volumes for better visualization.
• Cell Viewing Options: The GUI allows users to view only labeled cells, unlabeled cells, or all cells at once.Data Saving: The final labeled cells can be saved in .npy or .txt format for further use. This tool streamlines the process of annotating cells and ensures the creation of accurate training data for deep learning models..A video of the GUI has been provided for reference.