DetecTiff: a novel image analysis routine for high-content screening microscopy.
In this article, the authors describe the image analysis software DetecTiff, which allows fully automated object recognition and quantification from digital images. The core module of the LabView-based routine is an algorithm for structure recognition that employs intensity thresholding and size-dependent particle filtering from microscopic images in an iterative manner. Detected structures are converted into templates, which are used for quantitative image analysis. DetecTiff enables processing of multiple detection channels and provides functions for template organization and fast interpretation of acquired data. The authors demonstrate the applicability of DetecTiff for automated analysis of cellular uptake of fluorescence-labeled low-density lipoproteins as well as diverse other image data sets from a variety of biomedical applications. Moreover, the performance of DetecTiff is compared with preexisting image analysis tools. The results show that DetecTiff can be applied with high consistency for automated quantitative analysis of image data (e.g., from large-scale functional RNAi screening projects).
Gilbert
Daniel F
DF
Cell Biology/Biophysics Unit, EMBL, Heidelberg, Germany. gilbert@detectiff.com
Meinhof
Till
T
Pepperkok
Rainer
R
Runz
Heiko
H
D000465:Algorithms; D000818:Animals; D002478:Cells, Cultured; D003955:Diagnostic Tests, Routine / Q000379:methods; D006367:HeLa Cells; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D008853:Microscopy / Q000379:methods*; D010316:Particle Size; D010363:Pattern Recognition, Automated / Q000379:methods; D034622:RNA Interference / Q000502:physiology; D012984:Software; D014584:User-Computer Interface