LiDRoSIS: An Automated MATLAB-Python Platform for Image Processing and Quantitative Analysis of Lipid Droplets and ROS in Irradiated Cells

TL;DR

LiDRoSIS is an automated MATLAB-Python platform that enables high-throughput, reproducible analysis of lipid droplets and ROS in irradiated cells, integrating image processing with statistical analysis for radiobiological studies.

Contribution

It introduces a novel integrated MATLAB-Python software suite for automated segmentation and quantification of cellular components in microscopy images, enhancing research in nanomedicine and radiation biology.

Findings

Enables reproducible, high-throughput analysis of cellular features.

Combines classical image processing with statistical post-analysis.

Facilitates research linking nanoparticle exposure to radiobiological responses.

Abstract

LiDRoSIS is an automated MATLAB-Python software suite for the segmentation and quantification of lipid droplets (LDs) and reactive oxygen species (ROS) in fluorescence microscopy images of irradiated A549 and MCF7 cells exposed to gold-based nanoparticles. It combines classical image processing algorithms with statistical post-analysis through a companion Python tool, StatLysis. The platform enables reproducible, high-throughput analysis of morphological and spectral parameters linked to nanoparticle-enhanced radiobiological responses. By bridging imaging and quantitative analytics, LiDRoSIS provides a robust framework for nanomedicine and radiation biology research.