Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis
By Ahmad Paintdakhi, Bradley R. Parry, M. Campos, Irnov Irnov, Johan Elf, Ivan V. Surovtsev, C. Jacobs‐Wagner. Molecular Microbiology, 2015
373 citations recorded by the source corpus.
With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re‐emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single‐cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand‐alone, open‐source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non‐diffraction‐limited fluorescence signals and is scalable for high‐throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post‐processing analysis, makes the software broadly accessible to users irrespective of their computational skills.
Subfields: Biophysics, Structural Biology
View Paper: https://www.semanticscholar.org/paper/9c3d224d328ec5a44b24f87589232d8aed499c11
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Citations in the corpus
- MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis (2016, result): “Both the accuracy and the precision of MicrobeJ measurements are in accordance with those reported by other cell sub-pixel contour detection methods 8,9 (Supplementary Fig.”