17. Parameters¶
The different command line interfaces, or CLIs, (astec_fusion, astec_mars, etc.)
requires a parameter file (which is nothing but a python file) that contains
both information on the experiment (path to the experiment directory,
on the sub-directory names – see section Experiment parameters)
as well as specific parameters for the CLIs.
17.1. Prefixed parameters¶
Some of the parameter sets are said to be prefixed, such as the two sets of
pre-processing parameters for the astec_mars CLI
(see section astec_mars parameters).
Indeed, the pre-processing can be set differently for
the seed input image and the membrane input image (eg see section astec_mars).
Prefixing parameters allows to either set all the parameters with the same name together or set them independently.
As exemplified in section Steps 1 and 4: input image pre-processing, the parameter file lines (where the variables are not prefixed)
intensity_transformation = 'normalization_to_u8'
intensity_enhancement = None
will set the corresponding pre-processing parameters for both the seed and the membrane image pre-processing. However, using prefixes, as in the lines
seed_intensity_transformation = 'Identity'
membrane_intensity_transformation = 'normalization_to_u8'
intensity_enhancement = None
allows to set them independently.
This mechanism is designed to simplify the parameter file, but may have undesired consequences. Indeed, using the basic variable names of the registration parameters (see section Registration parameters) for the astec_astec CLI will change all registration parameters included in the pre-processing parameters.
To check whether the parameters have been set correctly, one can either use
the --print-param CLI option (see section Command line interfaces common options) beforehand, and/or to a posteriori check the used parameters in the log file.
17.2. Experiment parameters¶
17.2.1. Common parameters¶
PATH_EMBRYO:path to the experiment. If not present, the current directory is used. See section Fusion / input data, see figures Example 17.1, Example 17.2, Example 17.3, and Example 17.4
EN:the so-called embryo name. All files will be named after this name. E.g. see section Fusion / output data and figure Example 17.4.
first_time_pointfirst time point to be processed (
astec_fusion,astec_astecorastec_postcorrection) or single time point to be processed (astec_marsorastec_manualcorrection).beginsame as
first_time_pointlast_time_pointlast time point to be processed (
astec_fusion,astec_astecorastec_postcorrection).endsame as
last_time_pointrestart_time_pointtime point where to restart computation, used by astec_astec. Fragile.
delta_time_pointinterval between two time points to be processed. Set to 1 by default. Fragile.
deltasame as
delta_time_pointdelay_time_pointDelay to be added to the time points to build the file names. Fragile.
raw_delaysame as
delay_time_pointtime_digits_for_filenamenumber of digits used to build the file names.
time_digits_for_cell_idnumber of digits used to define unique cellule id. in the lineage/property file. The unique id of cell \(c\) at time \(t\) is \(t \times 10^d + c\) where \(d\) is set by
time_digits_for_cell_id.result_image_suffix:used for the result image data.
default_image_suffix:used for both the result and the temporary image data.
'inr': Inrimage format, kept for historical reasons.'mha': MetaImage format, readable by Fiji.'tif': not advised, since the tiff format does not allow to keep the voxel size along the z direction (aka spacing), at least in a standardized way.'nii': Nifti format, compatible with Omero.
Gzipped image files (with the additional extension
'.gz'are also readable.
result_lineage_suffix:
'pkl': pickle file
'xml': xml file
keep_auxiliary_filesorkeep_temporary_files:list of time points.
When fusing one time point,
astec_fusionkeeps temporary files in a directoryTEMP_<xxx>wherexxxdenotes the time point encoded into a three digit number. After fusion of the time point, this directory is erased.If
-koption (see Section 2.2) is passed toastec_fusion, all temporary directories TEMP_<xxx>` are kept. This may be of interest while investigating an unexpected behavior (see Section 6.11).However, when dealing with missing slices in acquisition data (see Section 5.1 and Section 5.2), it is needed to keep these temporary data for a few time points while processing the whole series. Passing the list of these time points to
keep_auxiliary_filesanswers this need.
17.2.2. Raw data directory parameters¶
DIR_RAWDATAsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
DIR_RAWDATA_CHANNEL_1see section Fusion / input data and 6.4.4
DIR_RAWDATA_CHANNEL_2see section Fusion / input data and 6.4.4
DIR_LEFTCAM_STACKZEROsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
DIR_LEFTCAM_STACKZERO_CHANNEL_1see section Fusion / input data and 6.4.4
DIR_LEFTCAM_STACKZERO_CHANNEL_2see section Fusion / input data and 6.4.4
DIR_RIGHTCAM_STACKZEROsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
DIR_RIGHTCAM_STACKZERO_CHANNEL_1see section Fusion / input data and 6.4.4
DIR_RIGHTCAM_STACKZERO_CHANNEL_2see section Fusion / input data and 6.4.4
DIR_LEFTCAM_STACKONEsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
DIR_LEFTCAM_STACKONE_CHANNEL_1see section Fusion / input data and 6.4.4
DIR_LEFTCAM_STACKONE_CHANNEL_2see section Fusion / input data and 6.4.4
DIR_RIGHTCAM_STACKONEsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
DIR_RIGHTCAM_STACKONE_CHANNEL_1see section Fusion / input data and 6.4.4
DIR_RIGHTCAM_STACKONE_CHANNEL_2see section Fusion / input data and 6.4.4
acquisition_leftcam_image_prefixsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
acquisition_rightcam_image_prefixsee section Fusion / input data, see figures Example 17.1, Example 17.2, and Example 17.3.
fusion_weightingsee section astec_fusion parameters
fusion_weighting_channel_1see section astec_fusion parameters
fusion_weighting_channel_2see section astec_fusion parameters
``<PATH_EMBRYO>``/
├── ``<DIR_RAWDATA>``/
│ ├── ``<DIR_LEFTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ ├── ``<acquisition_leftcam_image_prefix>001.zip``
│ │ └── ...
│ ├── ``<DIR_RIGHTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ ├── ``<acquisition_leftcam_image_prefix>001.zip``
│ │ └── ...
│ ├── ``<DIR_LEFTCAM_STACKONE>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ ├── ``<acquisition_leftcam_image_prefix>001.zip``
│ │ └── ...
│ └── ``<DIR_RIGHTCAM_STACKONE>``/
│ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ ├── ``<acquisition_leftcam_image_prefix>001.zip``
│ └── ...
...
``<PATH_EMBRYO>``/
├── ``<DIR_RAWDATA>``/
│ ├── ``<DIR_LEFTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_RIGHTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_LEFTCAM_STACKONE>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_RIGHTCAM_STACKONE>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_LEFTCAM_STACKZERO_CHANNEL_1>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_RIGHTCAM_STACKZERO_CHANNEL_1>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_LEFTCAM_STACKONE_CHANNEL_1>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ └── ``<DIR_RIGHTCAM_STACKONE_CHANNEL_1>``/
│ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ └── ...
...
``<PATH_EMBRYO>``/
├── ``<DIR_RAWDATA>``/
│ ├── ``<DIR_LEFTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_RIGHTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_LEFTCAM_STACKONE>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ └── ``<DIR_RIGHTCAM_STACKONE>``/
│ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ └── ...
├── ``<DIR_RAWDATA_CHANNEL_1>``/
│ ├── ``<DIR_LEFTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_RIGHTCAM_STACKZERO>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ ├── ``<DIR_LEFTCAM_STACKONE>``/
│ │ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ │ └── ...
│ └── ``<DIR_RIGHTCAM_STACKONE>``/
│ ├── ``<acquisition_leftcam_image_prefix>000.zip``
│ └── ...
...
17.2.3. Fusion directory parameters¶
EXP_FUSE:String (
strtype) or list (listtype) of strings. It indicates what are the fused images directories, of the form<PATH_EMBRYO>/FUSE/FUSE_<EXP_FUSE>.EXP_FUSE = 'exp1' EXP_FUSE = ['exp1', 'exp2']
are then both valid. Default value of
EXP_FUSEis'RELEASE'. See section Fusion / output data, see figure Example 17.4.
``<PATH_EMBRYO>``/
├── ``<DIR_RAWDATA>``/
│ └── ...
├── ``<FUSE>``/
│ └── ``FUSE_<EXP_FUSE>``/
│ ├── ``<EN>_fuse_t000.<result_image_suffix>``
│ ├── ``<EN>_fuse_t001.<result_image_suffix>``
│ └── ...
...
17.2.4. Drift directory parameters¶
EXP_DRIFT:String (
strtype). It serves to build the drift directory name, which is of the form<PATH_EMBRYO>/DRIFT/DRIFT_<EXP_DRIFT>. See astec_drift.
17.2.5. Contour directory parameters¶
EXP_CONTOUR:String (
strtype). It serves to build the drift directory name, which is of the form<PATH_EMBRYO>/CONTOUR/CONTOUR_<EXP_CONTOUR>. See Outer contour.
17.2.6. Membrane reconstruction directory parameters¶
EXP_RECONSTRUCTION:String (
strtype). It serves to build the membrane reconstruction directory name, which is of the form<PATH_EMBRYO>/REC-MEMBRANE/REC_<EXP_RECONSTRUCTION>. These images are used as elevation images for the watershed segmentation (used in both astec_mars and astec_astec). See also Image preprocessing. If not present in the parameter file, the value ofEXP_SEGis used instead.
17.2.7. Seed reconstruction directory parameters¶
EXP_RECONSTRUCTION:String (
strtype). It serves to build the seed reconstruction directory name, which is of the form<PATH_EMBRYO>/REC-SEED/REC_<EXP_RECONSTRUCTION>. These images are used to compute seeds for the watershed segmentation (used in both astec_mars and astec_astec). See also Image preprocessing. If not present in the parameter file, the value ofEXP_SEGis used instead.
17.2.8. Morphosnake reconstruction directory parameters¶
EXP_RECONSTRUCTION:String (
strtype). It serves to build the morphosnake reconstruction directory name, which is of the form<PATH_EMBRYO>/REC-MORPHOSNAKE/REC_<EXP_RECONSTRUCTION>. These images are used as support for the morphosnake correction (used in astec_astec, see Steps 5 and 6: morphosnake correction). See also Image preprocessing. If not present in the parameter file, the value ofEXP_SEGis used instead.
17.2.9. Mars directory parameters¶
EXP_MARS:String (
strtype). It serves to build the segmentation result directory name, which is of the form<PATH_EMBRYO>/SEG/SEG_<EXP_MARS>. See astec_mars. If not present in the parameter file, the value ofEXP_SEGis used instead.
17.2.10. Astec directory parameters¶
EXP_SEG:String (
strtype). It serves to build the segmentation result directory name, which is of the form<PATH_EMBRYO>/SEG/SEG_<EXP_SEG>. See astec_astec.
17.2.11. Post-processing directory parameters¶
EXP_POST:String (
strtype). It serves to build the post-segmentation result directory name, which is of the form<PATH_EMBRYO>/POST/POST_<EXP_POST>. See astec_postcorrection.
17.2.12. Intra-registration directory parameters¶
EXP_INTRAREG:String (
strtype). It serves to build the post-segmentation result directory name, which is of the form<PATH_EMBRYO>/INTRAREG/INTRAREG_<EXP_INTRAREG>. See astec_intraregistration.
17.3. Ace parameters¶
Ace stand for Automated Cell Extractor. [G[L]]ACE methods aim at detecting and enhancing membranes in a 3D images (see also section Membrane dedicated enhancement).
Hessian-based detection of 2-D manifolds, computation of a center-membrane image.
Thresholding of the center-membrane image to get a binary image.
Reconstruction of a membrane images from the binary image through tensor voting.
sigma_membranethis is the gaussian sigma that is used to compute image derivatives (in real units), for the Hessian-based detection of 2-D manifolds.
hard_thresholdingTrueorFalse. If set toTrue, a hard threshold (set by variablehard_threshold) is used instead of an automated threshold.
hard_threshold
manualTrueorFalse. By default, this parameter is set to False. If failure, (meaning that thresholds are very bad, meaning that the binarized image is very bad), set this parameter to True and relaunch the computation on the test image. If the method fails again, “play” with the value ofmanual_sigma… and good luck.manual_sigmaAxial histograms fitting initialization parameter for the computation of membrane image binarization axial thresholds (this parameter is used if
manualis set toTrue). One may need to test different values ofmanual_sigma. We suggest to test values between 5 and 25 in case of initial failure. Good luck.sensitivityMembrane binarization parameter. Use larger values (smaller than or equal to 1.0) to increase the quantity of binarized membranes to be used for tensor voting.
sigma_TVParameter which defines the voting scale for membrane structures propagation by tensor voting method (real coordinates). This parameter should be set between \(3 \mu m\) (little cells) and \(4.5 \mu m\) (big gaps in the binarized membrane image).
sigma_LF:Additional smoothing parameter for reconstructed image (in real coordinates). It seems that the default value = \(0.9 \mu m\) is ok for standard use.
sample:Set the fraction (in [0, 1]) of the binarized membranes further used for tensor voting. It allows tensor voting computation speed optimisation (do not touch if not bewared): the more sample, the higher the cost.
sample_random_seedDrawing a sample from the binarized membranes (see parameter
sample) is a stochastic process. Setting this parameter to someintvalue allows to make this stochastic process reproducible.ace_max_valueMaximal value for tensor voting output. After smoothing by
sigma_LF, the values are casted into 1 or 2 bytes depending on this maximal value.bounding_box_dilationDilation radius for the cell bounding boxes Used to compute local histograms
default_image_suffix
See also
Section Image preprocessing describes the overview of the so-called image reconstruction (ie how are build input images for segmentation).
Section Membrane dedicated enhancement gives some insights about membrane enhancement.
17.4. Morphosnake parameters¶
dilation_iterationsdilation of the cell bounding box for computation purpose.
iterationsmaximal number of morphosnake iterations.
delta_voxel:error on voxel count to define a stopping criteria.
energy'gradient': uses the same formula as in [MarquezNBA14], as in the historical astec version. But seems to be a poor choice.'image': uses directly the image as the energy image.
smoothing:internal parameter for the morphosnake.
balloon:internal parameter for the morphosnake.
processors: number of processors used for the morphosnake correction.
mimic_historical_astec:TrueorFalse. If set toTrue, same implementation than the historical astec version. Kept for comparison purpose.
17.5. Preprocessing parameters¶
The input image may be pre-processed before being used as
either the membrane image (ie the height image) for watershed segmentation,
or the seed image (ie the image with which the regional minima are computed),
or the morphosnake image (ie the image with which the morphosnake energy is computed).
For more details, see section Image preprocessing.
Ace parameters: see section Ace parameters.
intensity_prenormalization: possible values are'identity''normalization_to_u8''normalization_to_u16'
Performs a global robust normalization of the input image, prior to other pre-processing. The intensity value corresponding to the min percentile is set to 0, while the intensity value corresponding to the max percentile is set either to 255 (u8) or
prenormalization_max_value(u16). In-between values are linearly interpolated. Should be left to ‘identity’ for integer-encoded images. It has been introduced for real-encoded images.It is governed by the variables:
prenormalization_max_percentile: Percentile of the image histogram used to determine the value to be set to 0 (prenormalization step).prenormalization_min_percentile: Percentile of the image histogram used to determine the value to be set to maximal value (255 for u8,prenormalization_max_valuefor u16).prenormalization_max_value: Maximal output value to be issued from the prenormalization step (only used for theintensity_prenormalization = 'normalization_to_u16'case).
intensity_transformation: set the (histogram based) intensity transformation of the original image (see section Histogram based image value transformation)None: no intensity transformation of the original image is used to pre-process the input image.'identity': the input image is used without any transformation.'normalization_to_u8': the input image (usually encoded on 16 bits) is normalized onto 8 bits. The values corresponding to percentiles given by the variablesnormalization_min_percentileandnormalization_max_percentileare mapped respectively on 0 and 255.'normalization_to_u16': the input image (usually encoded on 16 bits) is normalized onto 8 bits or 16 bits. The values corresponding to percentiles given by the variablesnormalization_min_percentileandnormalization_max_percentileare mapped respectively on 0 and 255 for u8 ornormalization_max_valuefor u16).
intensity_enhancement: set the membrane enhancement transformation of the original image (see section Membrane dedicated enhancement)None: no membrane enhancement of the original image is used to pre-process the input image.'GACE': stands for Global Automated Cell Extractor. It tries to reconstructed a membrane image through a membrane detector, an automated thresholding and a tensor voting step. The automated thresholding is computed once for the whole image.'GLACE': stands for Grouped Local Automated Cell Extractor. It differs from one step fromGACE: the threshold of extrema image is not computed globally (as inGACE), but one threshold is computed per cell of \(S^{\star}_{t-1} \circ \mathcal{T}_{t-1 \leftarrow t}\), from the extrema values of the cell bounding box. This can be used only withastec_astec(section astec_astec).
outer_contour_enhancement: allows to use a fake outer contour for better segmentation of cells adjacent to the background.None: no contour images are used to pre-process the input image.'from_previous_segmentation': contour images are built from the previous segmented time point. Fragile. Kept for test purposes. Obviously, works only for propagated segmentation. This feature has been added for tests, but has not demonstrated yet any benefit.'from_contour_image': contours images named<EN>_contour_t<begin>.<image_suffix>are provided in a separate directory<PATH_EMBRYO>/CONTOUR/CONTOUR_<EXP_CONTOUR>/
reconstruction_images_combination:'addition''maximum'
normalization_min_percentilePercentile of the image histogram used to determine the value to be set to 0 (normalization step).normalization_max_percentilePercentile of the image histogram used to determine the value to be set to 255 or ‘normalization_max_value’ (normalization step)normalization_max_value: Maximal output value to be issued from the normalization step (only used for theintensity_normalization = 'normalization_to_u16'case).intensity_sigma: sigma (in real units) of the smoothing gaussian applied to the intensity-transformed image, prior its eventual combination with the other images (intensity enhancement, outer contours). Note that this variable can also be set by some watershed parameters (see section Watershed parameters and section A note on parameters).Registration parameters (see section Registration parameters) prefixed by
linear_registration_Registration parameters (see section Registration parameters) prefixed by
nonlinear_registration_save_reconstruction:TrueorFalse. If set toTrue, pre-processed images are kept in aRECONSTRUCTION/directory.These pre-processed images may be re-used in case of manual correction (see section astec_manualcorrection), to extract seeds and to do a watershed based segmentation when a cell is to be split. Thus, to spare computation time, it is advised to keep them.
17.6. Registration parameters¶
compute_registration:TrueorFalse.pyramid_highest_level: Registration is performed within a hierarchical scheme, ie an image pyramid is built, with the image dimensions decreasing from one pyramid level to the next (divided by 2). The registration starts at the highest pyramid level (the smallest image so the pyramid) and ends at the lowest level. 0 is the lowest level, ie the original image itself. To go from level ‘l’ to level ‘l+1’, each image dimension is divided by 2, meaning the size of a 3D image is divided by 8. Level 1 is defined by the first value of form ‘\(2^n\)’ immediately inferior to the image dimension, or the image dimension divided by 2 if it is already of form ‘\(2^n\)’. Setting this variable to 6 means that registration starts with images whose dimensions are 1/64th of the original image.pyramid_lowest_level: Lowest level of the pyramid image for registration. Setting it to 0 means that the lowest level is with the image itself. Setting it to 1, 2 or even 3 allows to gain substantial computational time. Seepyramid_highest_leveldescription.gaussian_pyramid:TrueorFalse. If True the image at one pyramid level is smoothed by a Gaussian kernel before building the image at the next level.transformation_typePossible values are'translation','rigid','similitude','affine'or'vectorfield'.elastic_sigma: Gaussian sigma to regularize the deformation, only for ‘vectorfield’ transformation. At each registration iteration, a residual deformation is computed. It is smoothed (regularized) by a gaussian offluid_sigmaparameter, then compounded with the previously found transformation, and the resulting deformation is finally smoothed (regularized) by a gaussian ofelastic_sigmaparameter.transformation_estimation_type: Possible values are'wlts','lts','wls', or'ls'.'wlts': weighted least trimmed squares'lts': least trimmed squares'wls': weighted least squares'ls': least squares
lts_fraction: Fraction of pairings retained to compute the transformation, only for robust estimation scheme ('wlts'or'lts'). Has obviously to be larger than 0.5.fluid_sigma: Gaussian sigma to regularize the deformation update, only for ‘vectorfield’ transformation. Seeelastic_sigmadescription.normalization:TrueorFalse. IfTrue, the images to be registered are normalized on 1 byte for computational purposes. This variable is kept for historical reasons. Do not change it.
17.7. Seed edition parameters¶
seed_edition_dir:seed_edition_file: if run with'-k', temporary files, including the computed seeds are kept into a temporary directory, and can be corrected in several roundsseed_edition_file = [['seeds_to_be_fused_001.txt', 'seeds_to_be_created_001.txt'], \ ['seeds_to_be_fused_002.txt', 'seeds_to_be_created_002.txt'], ... ['seeds_to_be_fused_00X.txt', 'seeds_to_be_created_00X.txt']]
Each line of a
seeds_to_be_fused_00x.txtfile contains the labels to be fused, e.g. “10 4 2 24”. A same label can be found in several lines, meaning that all the labels of these lines will be fused. Each line ofseeds_to_be_created_00x.txtcontains the coordinates of a seed to be added.
17.8. Watershed parameters¶
seed_sigma: gaussian sigma for smoothing of initial image for seed extraction (real coordinates). This is a short-cut to change the value ofintensity_sigmaof the pre-processing parameters used to get the seed image (see section Preprocessing parameters).seed_hmin: \(h\) value for the extraction of the \(h\)-minima,seed_high_threshold: regional minima thresholding.membrane_sigma: gaussian sigma for smoothing of reconstructed image for image regularization prior to segmentation (real coordinates). This is a short-cut to change the value ofintensity_sigmaof the pre-processing parameters used to get the membrane image (see section Preprocessing parameters).
17.9. Diagnosis parameters¶
These parameters are prefixed by diagnosis_.
minimal_volume: for diagnosis on cell volume. Threshold on cell volume. Snapshot cells that have a volume below this threshold are displayed.maximal_volume_variation: for diagnosis on cell volume. Threshold on volume variation along branches. Branches that have a volume variation above this threshold are displayed. The volume variation along a branch is calculated as \(100 * \frac{\max_{t} v(c_t) - \min_{t} v(c_t)}{\mathrm{med}_t v(c_t)}\) where \(v(c_t)\) is the volume of the cell \(c_t\) and \(\mathrm{med}\) is the median value.maximal_volume_derivative: for diagnosis on cell volume. Threshold on volume derivative along branches. Time points along branches that have a volume derivative above this threshold are displayed. The volume derivative along a branch is calculated as \(100 * \frac{v(c_{t+1}) - v(c_{t})}{v(c_{t})}\) where \(t\) denotes the successive acquisition time points.items: if strictly positif, number minimal of items (ie cells) to be displayed in diagnosis.minimal_length: for diagnosis on lineage. Threshold on branch length. Branches that have a length below this threshold are displayed.maximal_contact_distance: for diagnosis on cell contact surface. Threshold on cell contact surface distance along branches. Time points along branches that have a cell contact surface distance above this threshold are displayed (recall that the distance is in [0, 1]).
17.10. astec_fusion parameters¶
acquisition_orientation:'left'or'right'. Gives the rotation (with respect to the Y axis) of the left camera frame of stack #0 to be aligned with the the left camera frame of stack #1.'right': +90 degrees'left': -90 degrees
See also
'acquisition_mirrors'. Since it should depend on the apparatus, this parameter should not change for all acquisitions performed by the same microscope. See section Important parameters in the parameter file.acquisition_mirrors:TrueorFalse. IfFalse, the right camera images are mirrored to make them similar to left camera images. To determine the configuration (acquisition_orientation,acquisition_mirrors) (ie ('left',False), ('left',True), ('right',False), or ('right',True)), it is advised to perform the fusion for only one time point (by setting'begin'and'end'at the same value) with a large'target_resolution', for each of those 4 choices,xzsection_extractionbeing set toTrue(or some adequate value).See also
'acquisition_orientation'. Since it should depend on the apparatus, this parameter should not change for all acquisitions performed by the same microscope. See section Important parameters in the parameter file.acquisition_resolution: voxel size of acquired images e.g.raw_resolution = (.195, .195, 1.)
see section Important parameters in the parameter file.
acquisition_stack0_leftcamera_z_stacking:'direct'or'inverse'. Defines where are the high contrasted XZ-sections of the left camera image of stack0.'direct': small z are well contrasted (close to the camera), while large z are fuzzy. It is useful for direction-dependent weighting schemes.'inverse': the other way around.
Changing ‘direct’ to ‘inverse’ (or the other way) implies to change
acquisition_orientationas well. Settingxzsection_extractiontoTrue(or some adequate value) allows to verify whetheracquisition_stack0_leftcamera_z_stackingis set to the right value.acquisition_stack1_leftcamera_z_stacking: same asacquisition_stack0_leftcamera_z_stackingfor stack #1.acquisition_leftcamera_z_stacking: allows to set bothacquisition_stack0_leftcamera_z_stackingandacquisition_stack1_leftcamera_z_stacking. See section Important parameters in the parameter file.acquisition_slit_line_correction:TrueorFalse. Slit lines are Y lines that appear brighter or darker in the acquisition, which may cause artifacts in the reconstructed (ie fused) image, which, in turn, may impair further segmentation steps. See section Fusion method overview.target_resolution: Voxel size of the reconstructed image after fusion of the four views. e.g.target_resolution = 0.3
See section Fusion / output data.
fusion_strategy: Possible values are ‘direct-fusion’ and ‘hierarchical-fusion’.'direct-fusion': each acquisition is linearly co-registered with the first acquisition (stack #0, left camera). The transformation is computed in two steps:with parameters prefixed by
fusion_preregistration_(by default deactivated).with parameters prefixed by
fusion_registration_(by default'affine'transformation).
Then weights and images are transformed thanks to the computed transformations. Finally a weighted linear combination gives the result.
'hierarchical-fusion': from the couple (left camera, right camera), each stack is reconstructed following the same scheme than the direct fusion but with only 2 images. (thus with the registration parameters prefixed byfusion_preregistration_andfusion_registration_). Then stack #1 is co-registered with stack #0 in two steps:with parameters prefixed by
fusion_stack_preregistration_(by default'affine'transformation).with parameters prefixed by
fusion_stack_registration_(by default'vectorfield'transformation).
Images and weights associated with stack#1 are then transformed. Finally a weighted linear combination gives the result.
See section Step 5 parameters: image co-registration.
acquisition_cropping:True,False,'border'or'component'. If not set toFalse, the acquisitions stacks are cropped before fusion along the X and Y directions. Maximum Intensity Projection (MIP) images are automatically thresholded to determine the bounding box of the object of interest.Trueor'component': the largest 4-connected component is extracted from the MIP image, then an additional opening may be performed.'border': count the number of points above the threshold in rows or columns, and remove (from the border) the interval of rows (or columns) that contains less than 1% of the total count of points.
Margins are then added to the bounding box. See section Step 3 parameters: raw data cropping.
acquisition_z_cropping:True,False,'border'or'component'. If not set toFalse, the acquisitions stacks are cropped before fusion along the Z direction. Margins are then added to the bounding box.acquisition_cropping_margin_x_0: Added margin of the bounding box computed for the cropping of the raw acquisition image in ‘left’ X direction.acquisition_cropping_margin_x_1: Added margin of the bounding box computed for the cropping of the raw acquisition image in ‘right’ X direction.acquisition_cropping_margin_y_0: Added margin of the bounding box computed for the cropping of the raw acquisition image in ‘left’ Y direction.acquisition_cropping_margin_y_1: Added margin of the bounding box computed for the cropping of the raw acquisition image in ‘right’ Y direction.acquisition_cropping_margin_z_0: Added margin of the bounding box computed for the cropping of the raw acquisition image in ‘left’ Z direction.acquisition_cropping_margin_z_1: Added margin of the bounding box computed for the cropping of the raw acquisition image in ‘right’ Z direction.acquisition_cropping_margin_x: allows to set bothacquisition_cropping_margin_x_0andacquisition_cropping_margin_x_1acquisition_cropping_margin_y: allows to set bothacquisition_cropping_margin_y_0andacquisition_cropping_margin_y_1acquisition_cropping_margin_z: allows to set bothacquisition_cropping_margin_z_0andacquisition_cropping_margin_z_1acquisition_cropping_margin: allows to set the six margin variables.acquisition_cropping_opening: Active whenacquisition_croppingis set toTrueor'component'. Perform an opening (mathematical morphology) on the thresholded MIP image. It may be useful if some structures are connected to the desired one (0 means no opening, else specify the structuring element size).raw_cropsame asacquisition_croppingRegistration parameters (see section Registration parameters) prefixed by
fusion_preregistration_. First registration step of the co-registration of each of the four acquisitions for the'direct-fusion'scheme (seefusion_strategy), or of the left and right camera acquisitions to reconstruct a stack for the'hierarchical-fusion'scheme. By default deactivated.Registration parameters (see section Registration parameters) prefixed by
fusion_registration_. Second registration step of the co-registration of each of the four acquisitions for the'direct-fusion'scheme (seefusion_strategy), or of the left and right camera acquisitions to reconstruct a stack for the'hierarchical-fusion'scheme. By default an affine transformation is sought.Registration parameters (see section Registration parameters) prefixed by
fusion_stack_preregistration_. First registration step of the co-registration of the two stacks reconstructed with left and right cameras for the'hierarchical-fusion'scheme (seefusion_strategy). By default an affine transformation is sought.Registration parameters (see section Registration parameters) prefixed by
fusion_stack_registration_Second registration step of the co-registration of the two stacks reconstructed with left and right cameras for the'hierarchical-fusion'scheme (seefusion_strategy). By default an non-linear transformation is sought.xzsection_extraction:False,True, an integer or a list of integers.True: extracts the XZ-section at the middle of the volumeone integer: extracts the XZ-section for the given Y value
a list of integers: extracts the XZ-sections for all given Y values
Note
Setting the Y value(s) of the extracted XY sections allows to choose a convenient section for the fusion assessment.
If not
False, XZ-sections XZ-sections of the co-registered acquisitions, as well as the weighting function images, are stored in the directory<PATH_EMBRYO>/FUSE/FUSE_<EXP_FUSE>/XZSECTION_<xxxx>where<xxxx>is the time point index. It provides a direct and efficient means to check whether the parametersacquisition_orientation,acquisition_mirrors, oracquisition_stack[0,1]_leftcamera_z_stackingare correctly set. If the value is an integer or a list of integers, it indicates the indices of XZ-sections to be extracted See section Stacks non-linear co-registrationsave_transformation:TrueorFalse. IfTrue, the computed transformations are kept in directories<PATH_EMBRYO>/FUSE/FUSE_<EXP_FUSE>/TRSF_<xxxx>where<xxxx>is the time point index.fusion_cropping:True,False,'border'or'component'. If not set toFalse, the acquisitions stacks are cropped before fusion along the X and Y directions. Maximum Intensity Projection (MIP) images are automatically thresholded to determine the bounding box of the object of interest.Trueor'component': the largest 4-connected component is extracted from the MIP image, then an additional opening may be performed.'border': count the number of points above the threshold in rows or columns, and remove (from the border) the interval of rows (or columns) that contains less than 1% of the total count of points.
Margins are then added to the bounding box. See section Step 3 parameters: raw data cropping.
fusion_z_cropping:True,False,'border'or'component'. If not set toFalse, the fusion image is also cropped along the Z direction. Margins are then added to the bounding box.fusion_cropping_margin_x_0: Added margin of the bounding box computed for the cropping of the fusion image in ‘left’ X direction.fusion_cropping_margin_x_1Added margin of the bounding box computed for the cropping of the fusion image in ‘right’ X direction.fusion_cropping_margin_y_0Added margin of the bounding box computed for the cropping of the fusion image in ‘left’ Y direction.fusion_cropping_margin_y_1Added margin of the bounding box computed for the cropping of the fusion image in ‘right’ Y direction.fusion_cropping_margin_z_0Added margin of the bounding box computed for the cropping of the fusion image in ‘left’ Z direction.fusion_cropping_margin_z_1Added margin of the bounding box computed for the cropping of the fusion image in ‘right’ Z direction.fusion_cropping_margin_x: allows to set bothfusion_cropping_margin_x_0andfusion_cropping_margin_x_1fusion_cropping_margin_y: allows to set bothfusion_cropping_margin_y_0andfusion_cropping_margin_y_1fusion_cropping_margin_z: allows to set bothfusion_cropping_margin_z_0andfusion_cropping_margin_z_1fusion_cropping_margin: allows to set the six margin variables.fusion_weighting: Possible values are ‘uniform’, ‘ramp’, ‘corner’, or ‘guignard’. Allows to set the weighting function used to compute the weighted linear combination of the 4 co-registered acquisitions (for all channels to be processed).'uniform': uniform (or constant) weighting, it comes to the average of the resampled co-registered stacks'ramp': the weights are linearly increasing or decreasing along the Z axis'corner': the weights are constant in a corner portion of the stack, defined by two diagonals in the XZ-section'guignard': original historical weighting function, described in Leo Guignard’s Phd thesis [Gui15], that puts more weight to sections close to the camera and take also account the traversed material.
Setting the variable
xzsection_extractiontoTrue(or some adequate value) allows to see the weights used for the extracted XZ sections. See section Stacks non-linear co-registration.fusion_weighting_channel_0: set the weighting function for the weighted sum of the registered acquisition stacks for the first channel only (in case of multi-channel acquisition).fusion_weighting_channel_1: set the weighting function for the weighted sum of the registered acquisition stacks for the second channel only (in case of multi-channel acquisition).fusion_weighting_channel_2: set the weighting function for the weighted sum of the registered acquisition stacks for the third channel only (in case of multi-channel acquisition).
The following parameters are kept for backward compatibility:
fusion_cropsame asfusion_croppingfusion_margin_x_0same asfusion_cropping_margin_x_0fusion_margin_x_1same asfusion_cropping_margin_x_1fusion_margin_y_0same asfusion_cropping_margin_y_0fusion_margin_y_1same asfusion_cropping_margin_y_1fusion_xzsection_extractionsame asxzsection_extractionraw_cropsame asacquisition_croppingraw_margin_x_0same asacquisition_cropping_margin_x_0raw_margin_x_1same asacquisition_cropping_margin_x_1raw_margin_y_0same asacquisition_cropping_margin_y_0raw_margin_y_1same asacquisition_cropping_margin_y_1raw_mirrorssame asacquisition_mirrorsraw_orisame asacquisition_orientationraw_resolutionsame asacquisition_resolutionbegin: first time point of the series to be processed. See section Important parameters in the parameter file.deltaend: last time point of the series to be processed. When testing or tuning parameters, it is advised not to processed the whole series, but only one or a few time points. See section Important parameters in the parameter file.fusion_weightingfusion_weighting_channel_1fusion_weighting_channel_2fusion_weighting_channel_3raw_delay
17.11. astec_drift parameters¶
Intra-registration parameters (see section 17.16)
dilation_radius: defines the radius of the structuring element for dilation. Dilation will enlarge the membrane of the ‘i+1’ image, thus allow to compute the score wrt of the ‘i’ image defined as the enlarged membrane minus the ‘i’ image. Default value is 5.intensity_lower_quantile: defines the upper quantile of the fusion image to be used where computing the scores. It allows to select the hyper-intense areas (ie membranes). Default value is 0.1 (ie 10 %).intensity_upper_quantile: defines the upper quantile of the fusion image to be used where not computing the scores. It allows to remove the hyper-hyper-intense areas (ie fragments) that are not membranes. Default value is 0.002 (ie 0.2 %).only_initialisation: IfTrue, do not compute the corrections after the first intra-series registration. It allows to check whether the drift computation is required, or whether the fusion parameters have to be adjusted, or whether the drift parameters (egscore_threshold) have to be adjusted.score_threshold: defines a threshold on the ‘co-registration’ score. It allows first to select couples of images to be co-registered, and second to stop the co-registration procedure. If None, the threshold is automatically computed as the Otsu threshold from the scores.figurefile_suffix: suffix used to named the above python files as well as the generated figures.rotation_sphere_radius: Sphere radius to build the support of the rotation vector distribution. Any rotation is represented by a point inside a sphere of radius \(\pi\). Discretizing the sphere allows then to discretize the rotation space. The higher the radius, the more points inside the sphere, ie the more rotations to be tested (at a higher computational cost). Below are correspondances between the value of a radius (used to discretize a sphere in \(\mathbb{Z}^3\)) and the number of (rotation) vectors.radius = 3: 123 vectors, angle increment is 51.43 degrees
radius = 3.2: 147 vectors, angle increment is 49.15 degrees
radius = 3.4: 171 vectors, angle increment is 47.16 degrees
radius = 3.5: 179 vectors, angle increment is 45.41 degrees
radius = 3.7: 203 vectors, angle increment is 43.84 degrees
radius = 4.0: 257 vectors, angle increment is 40.00 degrees
radius = 4.2: 305 vectors, angle increment is 38.93 degrees
radius = 4.3: 341 vectors, angle increment is 37.95 degrees
radius = 4.4: 365 vectors, angle increment is 37.05 degrees
radius = 4.5: 389 vectors, angle increment is 36.20 degrees
radius = 4.6: 437 vectors, angle increment is 35.42 degrees
radius = 4.7: 461 vectors, angle increment is 34.68 degrees
radius = 4.9: 485 vectors, angle increment is 33.34 degrees
radius = 5.0: 515 vectors, angle increment is 32.73 degrees
radius = 5.1: 587 vectors, angle increment is 32.15 degrees
radius = 5.2: 619 vectors, angle increment is 31.60 degrees
radius = 5.4: 691 vectors, angle increment is 30.59 degrees
radius = 5.5: 739 vectors, angle increment is 30.11 degrees
radius = 5.7: 751 vectors, angle increment is 29.24 degrees
radius = 5.8: 799 vectors, angle increment is 28.83 degrees
radius = 5.9: 847 vectors, angle increment is 28.43 degrees
radius = 6.0: 925 vectors, angle increment is 27.69 degrees
Default value is 4.2.
corrections_to_be_done: acquisition time points to be corrected. Other time points, included those above the threshold, are ignored. For ‘i’ in the list, it means that the ith image is considered not being correctly registered with the (i+1)th one. However, setting the threshold for an earlier stop of computations is recommended.corrections_to_be_added: acquisition time points to be corrected (even if the corresponding score is below the threshold), in addition to the time points above the computed or given threshold. For ‘i’ in the list, it means that the ith image is not correctly registered with the (i+1)th one.corrections_to_be_skipped: acquisition time points not to be corrected (even if the corresponding score is above the threshold). For ‘i’ in the list, it means that the ith image is correctly registered with the (i+1)th one.
17.12. astec_mars parameters¶
These parameters are prefixed by mars_.
first_time_point: first time point to be segmented by the mars method. Overrides the value of thebeginvariable.last_time_point: last time point to be segmented by the mars method.Watershed parameters (see section Watershed parameters)
Seed edition parameters (see section Seed edition parameters)
Preprocessing parameters (see section Preprocessing parameters) prefixed by
seed_Preprocessing parameters (see section Preprocessing parameters) prefixed by
membrane_
17.13. astec_manualcorrection parameters¶
Diagnosis parameters (see section Diagnosis parameters)
Astec parameters (see section astec_astec parameters)
first_time_point: first time point to be corrected. Overrides the value of thebeginvariable.last_time_point: last time point to be corrected.input_image: defines the input file names (to be used when correcting other files than theastec_marsoutput file.output_image: defines the output file names (to be used when correcting other files than theastec_marsoutput file.manualcorrection_dir: path to directory where to find the mapping file.manualcorrection_file: path to mapping file for manual correction of a segmentation (ie label) image. See above the syntax of this file.1 line per label association
background label has value 1
the character
#denotes commented lines
Example of
mapping_file:# a line beginning by '#' is ignored (comment) # lines with only numbers concern changes for the first time point of the time series # or the only time point when correcting the segmentation of the first time point # - one single number: label of the cell to be divided at the first time point # - several numbers: labels of the cells to be fused # Hence 8 # means that cell of label 8 have to be splitted 9 2 7 # means that cells of label 9, 7, and 2 have to be fused 30 1 # means that cell of label 30 have to be fused with the background (of label 1) # lines beginning by 'timevalue:' concern changes for the given time point # - 'timevalue:' + one single number: label of the cell to be splitted # - 'timevalue:' + several numbers: labels of the cells to be fused # Note there is no space between the time point and ':' 8: 7 # means that cell of label 7 of time point 8 have to be splitted 10: 14 12 6 # means that cells of label 14, 12 and 6 of time point 10 have to be fused # lines beginning by 'timevalue-timevalue:' concern changes for the given time point range # - 'timevalue-timevalue:' + several numbers: labels of the cells to be fused 10-12: 14 16 # means that cells of label 14 and 16 of time point 10 have to be fused # their offspring will be fused until time point 12
new_division_trial: Number of trials (time points) to make a new division. If the division is not made at the targeted time point (from the provided file), another trial will be done at the nest time point (until the maximal number of trials is reached). Defaul value is 1.
17.14. astec_astec parameters¶
These parameters are prefixed by astec_.
Watershed parameters (see section Watershed parameters)
Preprocessing parameters (see section Preprocessing parameters) prefixed by
seed_Preprocessing parameters (see section Preprocessing parameters) prefixed by
membrane_Preprocessing parameters (see section Preprocessing parameters) prefixed by
morphosnake_Morphosnake parameters (see section Morphosnake parameters)
propagation_strategy:'seeds_from_previous_segmentation''seeds_selection_without_correction'
previous_seg_method: how to build the seeds \(S^e_{t-1 \leftarrow t}\) for the computation of \(\tilde{S}_{t}\)'deform_then_erode': \(S^{\star}_{t-1}\) is transformed towards \(I_t\) frame through \(\mathcal{T}_{t-1 \leftarrow t}\), and then the cells and the background are eroded.'erode_then_deform': historical method. The cells and the background of \(S^{\star}_{t-1}\) are eroded, and then transformed towards \(I_t\) frame through \(\mathcal{T}_{t-1 \leftarrow t}\).
previous_seg_erosion_cell_iterations: set the cell erosion size for \(S^e_{t-1 \leftarrow t}\) computation.previous_seg_erosion_background_iterations: set the background erosion size for \(S^e_{t-1 \leftarrow t}\) computation.previous_seg_erosion_cell_min_size: size threshold. Cells whose size is below this threshold will be discarded seeds in \(S^e_{t-1 \leftarrow t}\)watershed_seed_hmin_min_value: set the \(h_{min}\) value of the \([h_{min}, h_{max}]\) interval.watershed_seed_hmin_max_value: set the \(h_{max}\) value of the \([h_{min}, h_{max}]\) interval.watershed_seed_hmin_delta_valueset the \(\delta h\) to go from one \(h\) to the next in the \([h_{min}, h_{max}]\) interval.background_seed_from_hmin:TrueorFalse. Build the background seed at time point \(t\) by cell propagation.background_seed_from_previous:TrueorFalse. Build the background seed at time point \(t\) by using the background seed from \(S^e_{t-1 \leftarrow t}\). Fragile.seed_selection_tau: Set the \(\tau\) value for division decision (seed selection step).minimum_volume_unseeded_cell: Volume threshold for cells without found seeds in the seed selection step. Cells with volume (in \(\tilde{S}_t\)) whose size is below this threshold and for which no seed was found are discarded.volume_ratio_tolerance: Ratio threshold to decide whether there is a volume decrease (due to the background) for morphosnake correction.volume_ratio_threshold: Ratio threshold to decide whether there is a large volume decrease for segmentation consistency checking.volume_minimal_value: Size threshold for seed correction step. For a given cell at time point \(t-1\), if the corresponding cell(s) at time point \(t\) has(ve) volume below this threshold, they are discarded (and the cell at time point \(t-1\) has no lineage.morphosnake_correction:TrueorFalse.outer_correction_radius_opening
17.15. astec_postcorrection parameters¶
These parameters are prefixed by postcorrection_.
volume_minimal_valuebranch ending with leaf cell below this value are candidate for deletion. Expressed in voxel unit.lifespan_minimal_valuetest_early_divisiontest_volume_correlationcorrelation_thresholdtest_postponing_divisionpostponing_correlation_thresholdpostponing_minimal_lengthpostponing_window_lengthlineage_diagnosisperforms a kind of diagnosis on the lineage before and after the post-correction.
17.16. astec_intraregistration parameters¶
These parameters are prefixed by intra_registration_.
Registration parameters (see section Step 5 parameters: image co-registration)
reference_index: defines the still image after transformation compositions it will only translated, except ifreference_transformation_fileorreference_transformation_anglesare set. See section Step 3: template building.reference_transformation_file: resampling transformation to be applied to the reference image (and to the whole serie) after transformation compositions. See section Step 3: template building.reference_transformation_angles: list of rotations wrt the X, Y,or Z axis that defines the resampling transformation.reference_transformation_angles = 'X 30 Y 50'
represents a rotation of 30 degree around the X axis followed by a rotation of 50 degrees around the Y axis.
Beware: rotation composition depends on the order, so
'X 30 Y 50'is not equivalent to'Y 50 X 30'.template_typePossible values are ‘FUSION’, ‘SEGMENTATION’, or ‘POST-SEGMENTATION’ The template is built so that the useful information of all resampled images fits into it. Useful information can be issued from either the fused sequence, the segmentation sequence or the post-segmentation sequence.template_thresholdGiving a threshold with thetemplate_type, only points above the threshold are considered to be included in the template after resampling, this allows to reduce the template. According the background value is either 0 or 1 in both the segmentation and the post-segmentation sequences, setting this threshold to 2 for these sequences allows to keep the entire embryo in the resampled/reconstructed sequence.marginIn addition, a margin can be given for a more comfortable visualization. By default, it is 0 when only fusion images are used, and 10 if either segmentation or post-segmentation images are also used.resolutiongives the resulting (isotropic) voxel size (as the ‘target_resolution’ gives the voxel size of the fused images). However, for visualization purposes, it may be indicated to have a larger voxel size (hence the 0.6 instead of 0.3)rebuild_template:TrueorFalse. If set toTrue, force to recompute the template as well as the transformations from existing co-registrations (that are not re-computed). It is useful when a first intra-registration has been done with only the fusion images: a second intra-registration with the segmentation images as template can be done without recomputing the co-registrations.sigma_segmentation_imagesSigma to smooth (post-)segmentation images when resampling [ML25]resample_fusion_imagesPossible values areTrueorFalseresample_reconstruction_imagesPossible values areTrueorFalseresample_segmentation_imagesPossible values areTrueorFalseresample_post_segmentation_imagesPossible values areTrueorFalsemovie_fusion_imagesPossible values areTrueorFalse. To build 2D+t movies from the resampled fusion images.movie_segmentation_imagesPossible values areTrueorFalse. To build 2D+t movies from the resampled segmentation images.movie_post_segmentation_imagesPossible values areTrueorFalse. To build 2D+t movies from the resampled post-segmentation images.xy_movie_fusion_imagesList of XY-sections used to build the 2D+t movies egxy_movie_fusion_images = [100, 200]xz_movie_fusion_imagesList of XZ-sections used to build the 2D+t movies egxz_movie_fusion_images = [100, 200]yz_movie_fusion_imagesList of YZ-sections used to build the 2D+t movies egyz_movie_fusion_images = [100, 200]xy_movie_segmentation_imagesxz_movie_segmentation_imagesyz_movie_segmentation_imagesxy_movie_post_segmentation_imagesxz_movie_post_segmentation_imagesyz_movie_post_segmentation_imagesmaximum_fusion_imagesPossible values areTrueorFalse. Build a maximum image from the resampled series. It may be useful to define a cropping valid area for the whole sequence.maximum_segmentation_imagesmaximum_post_segmentation_images
17.17. astec_embryoproperties parameters¶
processors: Number of processors used to computed the properties. IfNone, all processors will be used. It allows parallel computations of properties (one image being processed by one processor) for the image sequence.max_chunks_properties: id asprocessors. Kept for back-compatibility.sigma_segmentation_smoothing: Gaussian standard deviation used to smooth segmentation images. Particulary important for surface estimation [ML25].