fastDDM: Accelerating Differential Dynamic Microscopy Analysis (poster)
Abstract
Overview: Differential Dynamic Microscopy (DDM) has emerged as a versatile and robust tool to quantify the dynamics of complex fluids and soft (biological) materials. It requires a microscope equipped with a digital camera and yields results analogous to those from multi-angle Dynamic Light Scattering experiments by analyzing microscopy movies of the sample.
Problem: A drawback of DDM is its time-consuming analysis and the lack of open optimized and user-friendly software.
Solution: Here, we introduce “fastDDM”, a Python library designed to enhance the accessibility and interactivity of DDM analysis. Employing cutting-edge algorithms and harnessing the computational power of GPUs, we achieve a remarkable reduction in the analysis time for standard image sequences (10,000 frames, 512x512 pixels) from hours to just seconds.
Examples: We will illustrate the capabilities of this software through practical examples drawn from existing literature, highlighting its potential to accelerate and simplify DDM analysis for researchers across various domains.'
