| Literature DB >> 18992251 |
Ying Chen1, Ena Ladi, Paul Herzmark, Ellen Robey, Badrinath Roysam.
Abstract
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%.Entities:
Mesh:
Year: 2008 PMID: 18992251 PMCID: PMC2646843 DOI: 10.1016/j.jim.2008.09.024
Source DB: PubMed Journal: J Immunol Methods ISSN: 0022-1759 Impact factor: 2.303