TLM-Converter: reorganization of long time-lapse microscopy datasets for downstream image analysis

Abstract

Automated microscopy enables in vivo studies in developmental biology over long periods of time. Time-lapse recordings in three or more dimensions to study the dynamics of developmental processes can produce huge data sets that extend into the terabyte range. However, depending on the available computational resources and software design, downstream processing of very large image data sets can become highly inefficient, if not impossible. To address the lack of available open source and commercial software tools to efficiently reorganize time-lapse data on a desktop computer with limited system resources, we developed TLM-Converter. The software either fragments oversized files or concatenates multiple files representing single time frames and saves the output files in open standard formats. Our application is undemanding on system resources as it does not require the whole data set to be loaded into the system memory. We tested our tool on time-lapse data sets of live Drosophila specimens recorded by laser scanning confocal microscopy. Image data reorganization dramatically enhances the productivity of time-lapse data processing and allows the use of downstream image analysis software that is unable to handle large data sets of ≤2 GB. In addition, saving the outputs in open standard image file formats enables data sharing between independently developed software tools.

Keywords

• Multidimensional imaging
• confocal laser scanning microscopy
• data reorganization
• time-lapse imaging