The MicrobeTracker grabs the parameters from the window at the beginning of any operation. Any changes made afterwards will have no effect. Not all of the
parameters are used for every operation, the rest are just ignored. Some of the parameters sets are saved as default, but they may need to be modified depending
on the particular image set. Usually only a few parameters have to be changed, these parameters are written in bold and their effect described in more detail
on the Adjusting Parameters page. Most of the parameters are numeric. The logical parameters
(yes/no) are also numeric, with yes=1 and no=0.
algorithm is the most important parameter, which
determines how the cells are outlined. For a more description of the difference
between algorithms see Cell outlining algorithms
section. If you are detecting cells in a timelapse series, the algorithm used
must be the same, the program will not be able to continue otherwise. Currently,
are implemented (numbered 1 to 4), though their quality of work and intended use
Algorithm 1 is the most primitive and the fastest algorithm
based exclusively on morphological operations, such as thresholding, edge
detection, and watershed algorithms. It is the closest to what most previous
object or cell detection program offered. This algorithm should be used when
nothing is known about the cell shape. However, if it tries to create a mesh
(which could be disabled with getmesh
parameter), it will not detect a cell if this is impossible for a particular
object. This algorithm uses a minimum number of parameters, only such parameters
interpoutline (and related),
parameters will affect detection.
The algorithms 2-4 use an attraction map, attracting the cell outline contour to particular points on the image, which is opposed by resistance related to
internal shape constraints. The nature of these constraints is different for each algorithm and is described below.
Algorithm 2 uses the same procedure as algorithm 1 for initial guess, which
is then refined using the Point Distribution Model (PDM). In timelapses, the
outline produced for the previous frame is used as the initial guess. This
algorithm is faster than the following algorithms and works only for the cells
which it is trained for. Currently only the data for "normal"
Caulobacter cells is included, but training is relatively simple and can
be performed by the user (see subsection Training).
Algorithm 3 is a modification of algorithm 2, though is uses a further
modified variant of the PDM to work on elongated cells. It currently requires
additional attention to develop the best parameter set and solve some common
Algorithm 4 is based on a version of the Active Contour Model (snake). It is
the slowest method and requires setting all parameters manually. It was
developed for filamentous cells, but is works well for all cell types. It is
recommended for the applications with filamentous cells and non-Caulobacter
rod-shaped cells. It will not work well for noticeably non-rod-shaped cells.
List of parameters
The most important parameters that should be changed relatively frequently are indicated in bold. The typical values are shown for wild type Caulobacter crescentus cells imaged in phase contrast regime at 0.064 μm/pixel resolution, unless mentioned otherwise.
- algorithm ─ the algorithm used, a number from 1 to 4, described above.
- invertimage (previously called useExtraData) ─ indicates that light cells are used on dark background and the image needs to be inverted (for example, if you are using diffuse GFP instead of phase contrast microscopy). All algorithms. Default: 0 (false).
Algorithm 1 specific
- getmesh ─ indicate
if mesh should be generated. Default: 1 (true).
- interpoutline ─
produce an interpolated outline instead of a pixilated one in order to achieve
subpixel resolution. When using interpolation, typically use with
fsmooth=Inf in order to not
smooth the outline additionally. Default: 0 (false).
- interpSigma ─
width of Gaussian smoothing (in pixels) applied in the interpolation
procedure. Consider values between 0 and 1-2 pixels.
- interpWeights ─
relative weights of the original image and edge strength in the interpolation
procedure, a vector of two values. Start with 0.5 0.5, then try from 0 1 to 1 0.
- areaMin ─ minimum area of the
region or the cell that is kept, all objects smaller will be discarded.
Depends on the resolution, select the smallest cell when detected to
- areaMax ─ maximum area of the
region or the cell that is kept, all regions larger will be attempted to
split, all cells larger will be discarded. The area of the cells depends on
the resolution. To estimate this parameter, set this value very large so
that no cells are rejected and click on the largest cell.
- splitregions ─ determines whether the
regions can be split using watershed algorithm, default value: 1 (meaning
- edgedetection (obsolete) ─ determines
whether the edge detection should be used (Laplacian of Gaussian algorithm),
default value is 1 (meaning "yes").
- edgemode ─
boundary (edge) detection method.
Currently a choice of "none" (or 0) - no edge detection, "log" (or 1) -
Laplacian of Gaussian (LoG) edge detection algorithm, "valley" (or 2) -
'valley detection' algorithm (zero crossings of the gradient), "logvalley"
(or 3) - both.
- edgeSigmaL (previously called
edgeSigma) ─ σ parameter of
Gaussian smoothing for the
LoG edge detection
- logthresh ─
threshold for the LoG edge detection algorithm. Default: 0. Typical values:
~0.1-0.4 (in the range 0 to 1).
- edgeSigmaV ─ σ parameter of
Gaussian smoothing for the
(previously called valleythres1) ─ weak threshold for the
Valley detection algorithm. Must be smaller than
(previously called valleythres2) ─ strong threshold for the
Valley detection algorithm.
- crossthresh ─
cross-detection threshold between the LoG and valley algorithms. Default: 0.
Typical values: ~0.1-0.4 (in the range 0 to 1).
- opennum ─ number of pixels to open (erode, then dilate) an image after segmentation to separate some of the cells that remained linked. Typical values from 0 to 3. Default - 0. For all algorithms.
─ image intensity (considering white is 0 and black is 1) threshold
factor, used in morphological operations. The value of 1 implies using the
automatically detected threshold. Increasing may help for some unevenly
illuminated images for which multiple false cells get detected. Typically
try increasing the values from 1 to 1.1-1.5. Increasing it too much can be
dangerous - if the automatically detected threshold multiplied by this value
exceeds the maximum bit depth of the image, the program will exit with an
─ an alternative to thresFactorM; this
factor tells the program the fraction of the brightest pixels to exclude
from threshold calculation. To eliminate the effect of bright dust particles
which may appear in the field of view. Default: 0, typical values:
- erodeNum ─ number of pixels to erode
from the cell before detection. Usually the value should be 1, but may be
increased if the cells tend to be detected smaller or missing the poles.
PDM model specific (for algorithms 2 and 3)
- scaleFactor ─ multiplication
factor to switch between different cameras or microscopes. Since cell
diameter cannot be set directly in the PDM model, this parameter is required
to use the same training file with different resolution images. For the
included training files (both for C. crescentus and E. coli,
the value 1 corresponds to the resolution 0.064 μm/pixel. In other
cases the parameter should be set to resolution / 0.064.
- trainingFile ─ file where the PDM
training data is saved.
- Nkeep ─ number of Principal Components
Analysis (PCA) modes to keep in a PDM-based algorithm. The default for
C. crescentus is 11, the number should be increased for more
complexly shaped cells and decteased for simpler shaped cells.
- rigidity ─ enhances the degree of
keeping constraints. Typical values from 0 to 0.1.
Constraints (for algorithm 4)
- cellwidth ─ typical width of the
- wspringconst the ─
"rigidity" of the cell width. This parameter has to be reduced
when measurements of the cell width or cell constriction are performed or if
the cell width is highly variable (typically from 0.5 to ~0.1).
- rigidityRange ─ the range of the cell
outline rigidity in pixels.
- rigidity ─ the value of the cell
outline rigidity. Reduce (from the default 0.4 for "normal" cells)
to pick roughness of the cell, increase for the cells to be smoother (for
example on rough background).
- rigidityRangeB ─ the range of the
backbone (centerline) rigidity in pixels.
- rigidityB ─ the value of the
backbone rigidity. Reduce for cells with kinks (default value is 4).
- horalign ─ parameter responsible for
maintaining perpendicular "ribs" during fitting. Only try changing
if cell outlines form self-intersections.
- eqaldist ─ parameter responsible for
maintaining equal spacing during fitting. Only try changing is cell outlines
Image forces (for algorithms 2-4)
- imageforce ─ factor, multiplying the
image attraction force (as opposed to constraints, see section
- attrCoeff ─ the force attracting
the contour to the dark areas outside of the cell. It is useful to fill the
cells on low contrast images, but may produce contours being detached from
the cell or noticeably larger, or the cells filling extra area after
splitting. In the latter cases the value has to be reduced to about 0-0.3.
Otherwise keep in the range 0.5 to 1 for algorithm 4. For algorithms 2 and 3
it should be ~10 times lower.
- repCoeff ─ the force repulsing
the contour from light areas inside the cell, for algorithms 2-4. It should
not exceed attrCoeff more than 3-4 times and has
to be increased if the contours are larger than the cells on some
- attrRegion ─ the width of the
attraction/repulsion area. Keep the default value (4) in most cases.
- forceWeights ─ relative weights of
different image force components (3 numbers in square brackets) in the
order: distance from the edge ─ gradient forces ─ attraction
to the intensity close to the threshold.
- dmapThres ─ threshold for the
distance from the edge method of force calculation (the force is a
sigmoid function of the distance, characterized by threshold and power
- dmapPower ─ power for the distance
from the edge method of force calculation.
- gradSmoothArea ─ the amount of smoothing
for the gradient forces method of force calculation.
- thresFactorF ─ similar to
thresFactorM, but used for the contour motion.
Keep equal to 1 in most cases, change together with
- repCoeff1 ─ similar to
repCoeff, but for the fit to the initial guess.
Keep 0 in most cases, except for very irregularly shaped cells, in that case
increase to ~1. For algorithms 2-3 only.
- attrCoeff1 ─ similar to
attrCoeff, but for the fit to the initial guess.
Keep 0 in most cases, except for very irregularly shaped cells, in that case
increase to ~1. For algorithms 2-3 only.
- repArea ─ maximum area of the cell when
it still experiences attraction as a fraction of
areaMax. Designed to use the attraction only for
falsely small cells.
- attrPower ─ the power in the sigmoid
function used in attraction.
- neighRep ─ the amount of repulsion from
previously detected neighbors in timelapses. Should be increases if cells
tend to grow into other cells area. If the growth between frames is
significant or if there is drift that cannot be eliminated by aligning
images, it may prevent the cells from occupying areas previously occupied by
the neighbors - the value should be reduced.
- neighRepA ─ similar to
neighRep, but uses a different way of taking
neighbors into account, should be 0 in most cases. For algorithm 4 only.
Contour fitting (for algorithms 2-4)
- fitDisplay ─ whether the images during
fitting should be displayed, for debugging purposes only.
- fitqualitymax ─ minimum allowed quality
of fit. Designed to reject not well fitted cells, but no efficient criterion
is currently implemented.
- fitDisplay1 ─ whether the cell should be
displayed during the fit for the initial guess. For debugging purposes. For
algorithms 2-3 only.
- fitConvLevel1 ─ one of the two possible
conditions to finish fitting to the initial guess if the norm of the force
drops below this value, usually not used. For algorithms 2-3 only.
- fitMaxIter1 ─ another condition to
finish, the maximum number of iterations in the initial guess fit. Rarely
changed. For algorithms 2-3 only.
- fitStep1 ─ the norm of the step size
when fitting to the initial guess. Rarely changed. For algorithms 2-3.
- fitConvLevel ─ one of the two possible
conditions to finish fitting if the norm of the force drops below this
value, usually not used.
- fitMaxIter ─ one of the conditions to
finish the fitting, the maximum number of iterations. Increase if you think
the contour has not converged yet; will be slower but more precise.
- moveall ─ whole cell motion coefficient,
linearly spanning between 0 and 1. 0 corresponds to growing non-moving cells
detection. 1 - the cell moving as a whole. For timelapses only. It is
recommended to set it below 1 even for moving cells for stability (i.e.
0.5-0.9). Setting it above 0 for non-moving cells helps if some drift of
pushing by other cells are present. For algorithm 4 only.
- fitStep ─ the norm of the step size.
Decrease if you the contour diverges, only helps if some of the force
parameter were increased.
- fitStepM ─ the norm of the step size of
the whole cell motion (in pixels). Typically about 1 is fine, decrease it if
the program is losing cells, increase if the outline does not shift
sufficiently from frame to frame. For algorithm 4 only.
- fmeshstep ─ distance between
"ribs" in the mesh in pixels, usually 1.
- fsmooth ─ number of Fourier modes
used to smooth the cell. The default for "normal" cells is 40,
this number has to be proportionally increased for filamentous cell (up to
~250 for very long cells). Values 0 or Inf will result in no smoothing.
- maxmesh ─ maximum size of the mesh. It
is mainly designed to reject meshes formed on clusters of cells, junk
particles or other large objects, keep the default value (1000) in most
- roiBorder ─ distance in pixels around
the existing mesh or detected region used to crop the corresponding image
area. Has to be larger than the cell can grow in one frame, if the cell can
be different from its initial guess.
- noCellBorder ─ distance from the edge of
the image the cells are not allowed to be in.
─ this parameter controls if a cell (which could in reality be a
cluster of cells) be rejected because of its proximity to the image edge
should be splitted to try getting a good cell. For algorithms 2-4. Default
- maxRegNumber ─ maximum number of regions
on a frame. Designed to prevent forming multiple regions in case of wrong
threshold detection. For a typical frame should be ~1000, depends on the
number of cells and image size. For algorithms 2-4.
- maxCellNumber ─ maximum number of cells
on a frame. Designed to prevent uncontrolled false divisions of some cells
in timelapses. For algorithms 2-4.
- meshStep ─ distance between ribs in the
- meshTolerance ─ Tthe precision of mesh
- meshWidth ─ typical width of the mesh,
used for mesh creation.
Joining and splitting
- splitThreshold ─ relative
threshold determining when the cell has to be split into two. Designed for
timelapse series, but can be used for independent images. Usually values
0.25-0.4 work for "normal" C. crescentus cells. Decrease if
cells don't split in time, and increase if they split too soon. For
- joindist ─ maximum distance in
pixels between cell poles when the program should try to join them. The
other condition is the angle between the backbones. The program will try
joining, but will keep the original shapes if it fails. For algorithms
- joinangle ─ maximum angle
between cell backbones in radians when the program should try to join them.
For algorithms 2-4.
- joinWhenReuse ─ whether the
program should try joining cells when reusing meshes. For algorithms
- split1 ─ whether the program
should try splitting cells on the first frame or independent images. For
- joindilate ─ the amount of dilation
(erosion) used when joining cells manually. The default is 1, it may have to
be reduced for long self-touching filamentous cells (using algorithm 4) to
-1 or -2.
- forceindframes (only in
Manual Operations regime) ─ if
this parameter is available and is equal to 1, it forces cell numbering in
time-lapse series to follow the rule of Individual Frames mode. New cells
aqcuire the smallest available numbers on the frame and the lineage data are
- bgrErodeNum ─ the number of pixels to
erode the image when detecting and subtracting the background. For
the background subtraction routine only.
- sgnResize ─ resizing when adding the
signal to increase the precision. Usually the effect is small at the cost of
increasing time. For the signal addition routine only.
- aligndepth ─ number of frames before
each image used during alignment. Default: 1. Increase beyond 1 to correct
for small drifts that accumulate into significant values in long time-lapse
series. Set this parameter to the typical number of frames required to drift
by 2-3 pixels. For the image alignment routine only.