Detects individual lipid droplets, usually clustered tightly.
Developped in Python.
The program takes a screening in BODIPY and HOESCHT channels as input and provides images of the segmentation of individual lipid droplets and associated nuclei. It also extracts several features such as the size distribution of the individual droplets per cell.
The aim is to improve models for High-Content/High-Throughput Microscopy Analysis of Subject-Specific Adipogenesis.
Modify the settings.py file to define the correct path, mostly input data.
In the main.py, you can chose the modules you want to apply. On the first run, apply them sequentially.
$ python main.py
This algorithm needs CellProfiler to define the relationship between nuclei and associated lipid droplets, i.e., approximated the cells.
http://cellprofiler.org/releases/
This project was funded by Science for Life Laboratory, the Swedish research council (grant 2012-4968 to Carolina Wählby and K2012-55X-010334-46-5 to Peter Arner), the Swedish strategic research program eSSENCE (to Carolina Wählby) and CIMED (to Peter Arner).
Copyright (c) 2016-2017, Maxime Bombrun
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