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Showing papers by "Andrew Rabinovich published in 2006"


Proceedings ArticleDOI
17 Jun 2006
TL;DR: A framework for visual grouping that frees the user from the hassles of parameter tuning and model order selection and a new characterization of the space of stabilities for a continuum of segmentations that provides for an efficient sampling scheme.
Abstract: Model order selection and cue combination are both difficult open problems in the area of clustering. In this work we build upon stability-based approaches to develop a new method for automatic model order selection and cue combination with applications to visual grouping. Novel features of our approach include the ability to detect multiple stable clusterings (instead of only one), a simpler means of calculating stability that does not require training a classifier, and a new characterization of the space of stabilities for a continuum of segmentations that provides for an efficient sampling scheme. Our contribution is a framework for visual grouping that frees the user from the hassles of parameter tuning and model order selection: the input is an image, the output is a shortlist of segmentations.

57 citations


Journal ArticleDOI
TL;DR: Advances in living cellular fluorescence biosensors and computerized microscopy enable a vision of fully automated high‐resolution measurements of the detailed intracellular molecular dynamics directly linked to cellular behaviors.
Abstract: Background: Advances in living cellular fluorescence biosensors and computerized microscopy enable a vision of fully automated high-resolution measurements of the detailed intracellular molecular dynamics directly linked to cellular behaviors. Given the heterogeneity of cell populations, a statistically relevant study of molecular-cellular dynamics is a key motivation for improved automation. Methods: We explored automating computerized, microscope-based data extraction and analyses that monitor cell locomotion, rates of mitoses, and spatiotemporal activities of intracellular proteins via ratiometric fluorescent biosensors in mouse fibroblasts. Novel image processing methods included K-means clustering segmentation preprocessing followed by modified discrete, normalized cross-correlational alignment of two-color images; ratiometric processing for fluorescence resonance energy transfer (FRET) measurements; and intracellular spatial distribution measurements of RhoA GTPase activity. Results: The interdivision time was 19.4 h (mean) ± 6.0 h (SD) (n = 7) for the GFP-histone cells in the two-by-two field that was scanned for 72 h. After registration and ratioing of the cells with the RhoA biosensor, increases in both cell protrusion and retraction were coincident with to increases in RhoA activity. Conclusions: These advances lay the foundation for extracting and correlating measurements characterizing the functional relationships of spatial localization and protein activation with features of cell migration such as velocity, polarization, protrusion, retraction, and mitosis. © 2006 International Society for Analytical Cytology

36 citations