- Cellprofiler saving images manual#
- Cellprofiler saving images software#
- Cellprofiler saving images series#
For example, “27-34” refers to object 34 in image 27.
Cellprofiler saving images series#
The user interface and its associated controller classes access and modify the data model.Įvery object in the series has a unique identifier that includes its image number and the object number in that frame, which is assigned by CellProfiler or created while importing data from Icy or Fiji/TrackMate. Traxtile maintains a data model that includes a list of all cells identified in each frame of a time series and the relationships between cells in successive frames. In contrast to existing track editing platforms, Traxtile supports interactive editing of cell tracks on zoomed images of cells undergoing sentinel events such as cell division and cell death.
Cellprofiler saving images software#
Traxtile was designed as an adjunct to CellProfiler and other cell tracking software to provide a convenient visual platform for reviewing and editing object tracks in the context of time series images. The Traxtile program was developed as a tool for directly measuring rates of cell division and death, by observing these events under various conditions using time-lapse imaging.
Cellprofiler saving images manual#
Furthermore, while track editing is available in other tracking software platforms, such as Icy and Fiji, these interfaces are limited when it comes to manual review of cell division and death. This validation step is not easy to accomplish with CellProfiler, which at this time produces only tabular summaries of recognized objects and tracks. This requires manual review of images to determine whether a track that splits represents a true cell division or whether a track that appears to end represents a true cell death. Thus, for rigorous quantitation of cell division and death kinetics, events must be validated. However, for any system, tracking assignments are often imperfect, and rare events can be obscured even when error rates are low ( 4, 5). These applications include CellProfiler, which provides a suite of image analysis tools through a powerful and flexible interface ( 1), as well as other freely available software packages that provide similar functionality, such as Fiji and Icy ( 2, 3). There are convenient platforms for loading time-lapse image series, optimizing image contrast, recognizing objects (e.g., cells) in each image, and tracking objects through time. Cell division and death are regulated by distinct biochemical networks, so this uncertainty creates a barrier to understanding basic mechanisms that regulate cell numbers in health and disease. However, it is often unclear whether an observed difference in the overall population growth rate is due to a change in the rate of cell division or in the rate of cell death. It is well known that average growth rates can be influenced by environmental conditions such as the availability of growth factors and nutrients, and by intrinsic factors such as cell genotype. The growth rate of a cell population is determined by the rates of cell division and death. Traxtile is implemented in Python version 2.7 using standard distribution libraries (available at and is freely available at. Reports summarize events from the validated tracks. Links between cells in successive frames can be reviewed and edited, yielding validated tracks for the image series.
For each such event, the object track is displayed on a montage of images centered on the event and spanning the preceding and subsequent frames. Traxtile imports initial assignments and automatically identifies events needing review (i.e., apparent creation of new objects, splits, merges, and losses). Here we describe Traxtile, a program that allows interactive graphical review and revision of object tracking assignments. This is challenging, as CellProfiler produces only tabular data for object tracking, and the graphical tools in Icy and Fiji are not optimal for manual review of these events. However, object tracking algorithms are imperfect, and validation of significant events is often required. Open source software packages such as CellProfiler, Icy, and Fiji provide robust and convenient interfaces for performing such analyses. Time-lapse imaging can be used to quantify how cells move, divide, and die over time and under defined culture conditions.
0 kommentar(er)
