6533b7cffe1ef96bd1258c91

RESEARCH PRODUCT

Fuzzy temporal random sets with an application to cell biology

Derek ToomreRoberto ZoncuTeresa LeónGuillermo AyalaRafael SebastianM. E. Díaz

subject

business.industryBinary imageFuzzy setPattern recognitionFunction (mathematics)Image segmentationFuzzy logicThresholdingSet (abstract data type)Computer visionArtificial intelligencebusinessIndependence (probability theory)Mathematics

description

Total Internal Reflection Fluorescence Microscopy (TIRFM) greatly facilitates to imaging the first steps of endocytosis, a process whereby cells traffic cargo from the cell surface to endosomes. Using TIRFM, fluorescent-tagged endocytic proteins are observed as overlapped areas forming random clumps of different sizes, shapes and durations. A common procedure to segment these objects consists of thresholding the original gray-level images to produce binary sequences in which a pixel is covered or not by a given fluorescent-tagged protein. This binary logic is not appropriate because it leaves a free tuning parameter to be set by the user which can influence on the conclusions of the statistical analysis. Instead, we have adopted a more realistic approach, in which segmented binary images are modelled as a fuzzy temporal random set. Here, we propose some measures of spatio-temporal interactions based on the fuzzy counterparts of the pair-correlation function and the Ripley K-function. We used a randomization procedure to test for independence. Our results show that this procedure will permit biologists to examine and quantify the interactions between endocytic proteins robustly.

https://doi.org/10.1109/fuzzy.2007.4295484