Quantifying cellular interaction dynamics in 3D fluorescence microscopy data Export

@article{citeulike:5996287, abstract = {The wealth of information available from advanced fluorescence imaging techniques used to analyze biological processes with high spatial and temporal resolution calls for high-throughput image analysis methods. Here, we describe a fully automated approach to analyzing cellular interaction behavior in 3D fluorescence microscopy images. As example application, we present the analysis of drug-induced and S1P1-knockout-related changes in bone–osteoclast interactions. Moreover, we apply our approach to images showing the spatial association of dendritic cells with the fibroblastic reticular cell network within lymph nodes and to microscopy data regarding T–B lymphocyte synapse formation. Such analyses that yield important information about the molecular mechanisms determining cellular interaction behavior would be very difficult to perform with approaches that rely on manual/semi-automated analyses. This protocol integrates adaptive threshold segmentation, object detection, adaptive color channel merging, and neighborhood analysis and permits rapid, standardized, quantitative analysis and comparison of the relevant features in large data sets.}, author = {Klauschen, Frederick and Ishii, Masaru and Qi, Hai and Bajenoff, Marc and Egen, Jackson G. and Germain, Ronald N. and Meier-Schellersheim, Martin}, citeulike-article-id = {5996287}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nprot.2009.129}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nprot.2009.129}, day = {20}, doi = {10.1038/nprot.2009.129}, issn = {1754-2189}, journal = {Nature Protocols}, keywords = {3d, cell-biology, data-analysis, microscopy}, month = {August}, number = {9}, pages = {1305--1311}, posted-at = {2009-10-23 03:53:36}, priority = {2}, publisher = {Nature Publishing Group}, title = {Quantifying cellular interaction dynamics in 3D fluorescence microscopy data}, url = {http://dx.doi.org/10.1038/nprot.2009.129}, volume = {4}, year = {2009} }

TY - JOUR ID - citeulike:5996287 L3 - citeulike-article-id:5996287 N2 - The wealth of information available from advanced fluorescence imaging techniques used to analyze biological processes with high spatial and temporal resolution calls for high-throughput image analysis methods. Here, we describe a fully automated approach to analyzing cellular interaction behavior in 3D fluorescence microscopy images. As example application, we present the analysis of drug-induced and S1P1-knockout-related changes in bone–osteoclast interactions. Moreover, we apply our approach to images showing the spatial association of dendritic cells with the fibroblastic reticular cell network within lymph nodes and to microscopy data regarding T–B lymphocyte synapse formation. Such analyses that yield important information about the molecular mechanisms determining cellular interaction behavior would be very difficult to perform with approaches that rely on manual/semi-automated analyses. This protocol integrates adaptive threshold segmentation, object detection, adaptive color channel merging, and neighborhood analysis and permits rapid, standardized, quantitative analysis and comparison of the relevant features in large data sets. IS - 9 JF - Nature Protocols SN - 1754-2189 EP - 1311 TI - Quantifying cellular interaction dynamics in 3D fluorescence microscopy data PB - Nature Publishing Group VL - 4 SP - 1305 KW - 3d KW - cell-biology KW - data-analysis KW - microscopy AU - Klauschen, Frederick AU - Ishii, Masaru AU - Qi, Hai AU - Bajenoff, Marc AU - Egen, Jackson AU - Germain, Ronald AU - Meier-Schellersheim, Martin PY - 2009/08/20/ UR - http://dx.doi.org/10.1038/nprot.2009.129 ER -