Quimp3, an automated pseudopod-tracking algorithm

L Bosgraaf, PJM Van Haastert - Cell adhesion & migration, 2010 - Taylor & Francis
L Bosgraaf, PJM Van Haastert
Cell adhesion & migration, 2010Taylor & Francis
To understand movement of amoeboid cells we have developed an information tool that
automatically detects protrusions of moving cells. The algorithm uses digitized cell
recordings at a speed of~ 1 image per second that are analyzed in three steps. In the first
part, the outline of a cell is defined as a polygon of~ 150 nodes, using the previously
published Quimp2 program. By comparing the position of the nodes in place and time, each
node contains information on position, local curvature and speed of movement. The second …
To understand movement of amoeboid cells we have developed an information tool that automatically detects protrusions of moving cells. The algorithm uses digitized cell recordings at a speed of ~1 image per second that are analyzed in three steps. In the first part, the outline of a cell is defined as a polygon of ~150 nodes, using the previously published Quimp2 program. By comparing the position of the nodes in place and time, each node contains information on position, local curvature and speed of movement. The second part uses rules for curvature and movement to define the position and time of start and end of a growing pseudopod. This part of the algorithm produces quantitative data on size, surface area, lifetime, frequency, and direction of pseudopod extension. The third part of the algorithm assigns qualitative properties to each pseudopod. It decides on the origin of a pseudopod as splitting of an existing pseudopod or as extension de novo. It also decides on the fate of each pseudopod as merged with the cell body or retracted. Here we describe the pseudopod tool and present the first data based on the analysis of ~1000 pseudopodia extended by Dictyostelium cells in the absence of external cues.
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