Tomocube

1. Pipeline: (3D) Lipid Droplet

This pipeline segments and quantifies lipid droplets (LDs) across the entire sample using a rule-based algorithm optimized for holotomography (HT) data. It identifies lipid droplets based on their distinct morphological and optical properties, including high refractive index (RI) values and a consistently round shape.

The pipeline supports both global and object-level quantification. It calculates the total and average values of lipid droplet measurements, such as volume and count, across the full field of view. In addition, each individual LD is assigned a unique ID, enabling detailed analysis of its size, shape, and spatial position. This dual-level approach allows researchers to assess overall lipid accumulation while also exploring heterogeneity among individual droplets in high-resolution 3D images.

Output: Total LD mask and individual LD masks, Total LD measurements within the field of view(FOV), Individual LD measurements
 

This pipeline segments lipid droplets (LDs) in 2D projections using a rule-based algorithm that leverages their distinct morphological and optical characteristics. Lipid droplets are identified based on their high refractive index (RI) values and round shape, allowing for accurate detection without the need for AI models.

Optimized for label-free holotomographic imaging, this pipeline enables efficient and reproducible LD analysis across various sample types. It is particularly useful for applications requiring fast LD quantification in large datasets or where computational simplicity is preferred.

Output: Segmented LD masks in 2D, Individual LD labels, LD measurements

Access to analysis pipelines is available upon request. Please send your inquiry to info@tomocube.com to explore the options best suited to your needs.