Automated Analysis of the Mitotic Phases of Human Cells in 3D Fluorescence Microscopy Image Sequences Export

@incollection{citeulike:2204800, abstract = {The evaluation of fluorescence microscopy images acquired in high-throughput cell phenotype screens constitutes a substantial bottleneck and motivates the development of automated image analysis methods. Here we introduce a computational scheme to process 3D multi-cell time-lapse images as they are produced in large-scale RNAi experiments. We describe an approach to automatically segment, track, and classify cell nuclei into different mitotic phases. This enables automated analysis of the duration of single phases of the cell life cycle and thus the identification of cell cultures that show an abnormal mitotic behavior. Our scheme proves a high accuracy, suggesting a promising future for automating the evaluation of high-throughput experiments.}, author = {Harder, Nathalie and Mora-Berm\'{u}dez, Felipe and Godinez, William and Ellenberg, Jan and Eils, Roland and Rohr, Karl}, citeulike-article-id = {2204800}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/11866565_103}, doi = {10.1007/11866565_103}, journal = {Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006}, keywords = {cell, tracking}, pages = {840--848}, posted-at = {2008-01-07 20:08:02}, priority = {0}, title = {Automated Analysis of the Mitotic Phases of Human Cells in 3D Fluorescence Microscopy Image Sequences}, url = {http://dx.doi.org/10.1007/11866565_103}, year = {2006} }

TY - CHAP ID - citeulike:2204800 L3 - citeulike-article-id:2204800 N2 - The evaluation of fluorescence microscopy images acquired in high-throughput cell phenotype screens constitutes a substantial bottleneck and motivates the development of automated image analysis methods. Here we introduce a computational scheme to process 3D multi-cell time-lapse images as they are produced in large-scale RNAi experiments. We describe an approach to automatically segment, track, and classify cell nuclei into different mitotic phases. This enables automated analysis of the duration of single phases of the cell life cycle and thus the identification of cell cultures that show an abnormal mitotic behavior. Our scheme proves a high accuracy, suggesting a promising future for automating the evaluation of high-throughput experiments. JF - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006 EP - 848 TI - Automated Analysis of the Mitotic Phases of Human Cells in 3D Fluorescence Microscopy Image Sequences SP - 840 KW - cell KW - tracking AU - Harder, Nathalie AU - Mora-Bermúdez, Felipe AU - Godinez, William AU - Ellenberg, Jan AU - Eils, Roland AU - Rohr, Karl PY - 2006/// UR - http://dx.doi.org/10.1007/11866565_103 ER -