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pubmed:abstractText |
This paper presents automated methods to quantify dynamic phenomena such as cell-cell interactions and cell migration patterns from time-lapse series of multi-channel three-dimensional image stacks of living specimens. Various 5-dimensional (x, y, z, t, lambda) images containing dendritic cells (DC), and T-cells or thymocytes in the developing mouse thymic cortex and lymph node were acquired by two-photon laser scanning microscopy (TPLSM). The cells were delineated automatically using a mean-shift clustering algorithm. This enables morphological measurements to be computed. A robust multiple-hypothesis tracking algorithm was used to track thymocytes (the DC were stationary). The tracking data enable dynamic measurements to be computed, including migratory patterns of thymocytes, and duration of thymocyte-DC contacts. Software was developed for efficient inspection, corrective editing, and validation of the automated analysis results. Our software-generated results agreed with manually generated measurements to within 8%.
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pubmed:affiliation |
Department of Electrical, Computer, and System Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, Non-P.H.S.,
Research Support, N.I.H., Extramural
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