Image processing functions in Image Analyst MKII
Image Analyst MKIIFunctions Glossary
HomeWorkflowImage Processing BasicsFunctions GlossaryPipelines GlossaryProtocolsQuick How ToSearch
2D DFT Filter
2D DFT Filter Butterworth BP
2D DFT Filter Butterworth BP Tiled
2D Kernel Convolution
2D Median
2D Morphological Operator
2D Nonlinear Filter
2D Savitzky-Golay filter
Absolute Value
Affine Transformation
Align Channels
Align Series (Image Stabilizer)
Align Tiled Channels
Align Tiled Series (Image Stabilizer)
Anisotropic Diffusion Filter
Attach Intensity Gating Image
Attach Overlay Image
Automatic ROI drawing
Band Pass filter Optimization
Blind Spectral Unmix with NMF
Calculate Simple Crossbleed
Calculate Spatial Moments
Calibration Wizard Parameters
Clear Segmentation Classifiers
Close Image Window
Copy Image Window
Copy ROIs from Other Image
Correct Intensity Jump
Correct Lens Distortion
Count Division and Cell Death
Count Object Colocalization
Create ROI
Create ROIs from Segments
Crop
Crop Image in Place
Crop Image to Segments
Cross-correlation data
Cross-correlation image
Detect Nuclei Convolution
Differential Evolution Optimizer
Distance from Segments
Draw Model Mitochondrion
Draw Random Position Model Mitochondria
EndIf
Erase All ROIs
Excel Window Command
Export
Fill Mask
Fill or Mask Active ROI
FLIPR Calibration with [K+]ec steps and known [K+]ic and known kP
FLIPR Complete Calibration
FLIPR Complete Calibration with known kP
FLIPR Complete Calibration with known kP - Goldman
FLIPR Complete Iterative Calibration
FLIPR Estimate PN
FLIPR Short Calibration based on known potential during MDC and CDC
FLIPR Short Calibration between known baseline and CDC
FLIPR Short Calibration between known baseline and MDC
FLIPR Short Calibration between known baseline and separately measured fP0
FLIPR Short Calibration from Zero with fx=0
FunctionOptions
Get Image Information
Get Linked Channel
If
If Greater Than Zero
Image Arithmetic (image-image math)
Image Arithmetic In Place
Image Arithmetic Single Frame
Inpaint Mask
Input
Invert
Lens Correction Optimization
Link Image Windows
Load and Run Pipeline
Load ROIs
Mask Borders
Mask Frames by Plot Values
Mask Images
Measure Object Intensity
Measure Object Morphology
Mirror or Rotate (new image)
Mirror or Rotate in Place
Multi-Dimensional Open Information
Multi-Dimensional Open Stage Position
Multi-Dimensional Reload Channel
New Image
New Time Scale
Onset Image
Open File
Optical Flow
Options
Pipeline
Pipeline Optimization
Pipeline Optimization Parameter
Plot
Plot Correlation (Colocalization)
Plot Intensities Corresponding to Segments
Plot Morphological Parameters of Segments
Plot Ratio
Plot ROI Dimensions
Plot Tracking Parameters
Potential calibration constants
Potential calibration error propagation
Potential calibration expert overrides
Projection of Vectors from a Point
Ratio
Ratiometric ROI Classifiers
ReCount Division and Cell Death
Reevaluate Segments
Remove Blank Frames
Rename
Resample Image
ROI Classifiers
Run Membrane Potential Calibration
Save ROIs
Scalar Arithmetic (image-value math)
Scalar Arithmetic Multi
Secondary Watershed Segmentation
Select
Select by Number
Sensor Noise Characteristics
Set Reference Image
Set Scaling/LUT
Set Segmentation Classifiers
Set Segmentation Intensity Classifiers
Shift Time Scale
Simple 2D Cross-correlation
Simple Segmentation
Skeletonize
Spectral Unmix
Strip to Well Cell Count
Substitute Poisson Noise
Subtract Background or Normalize
T or Z-project
Template Matching
Temporal Average Filter
Temporal Block Filter
Temporal Median Filter
Temporal Rolling Projection
Temporal Savitzky-Golay Filter
Thinness Ratio Optimization
Threshold
Time Stamp and Scale Bar
TMRM Complete Calibration
TMRM Complete Calibration with known kT
TMRM Complete Calibration with known kT and K-steps
TMRM Short Calibration between known baseline and MDC or CDC
Track Objects
Truncate or Cut
Wait for All Inputs
Watershed Segmentation
Wiener filter
Window Menu Command
Write Back Scaled Values
ΔF/F0

Track Objects ( IATrackObjects )

Parameters:
Name Short Name Type Description
Type of Algorithm type string
Number of iterations iterations integer
Random seed rndseed integer
Group size diameter groupsize real Distance in pixels of centers objects before fusion or after division, before recursion. 0 = no grouping.
Maximal group area maxgruparea integer Maximal area of groups after recursion. 0 = not applied
Group recursion rndseed integer 0 or 1 means no recursion, 2 regroups groups once...
Group max energy (intensity RMS) groupmaxenergy real Mean of normalized E_mean_intensity
Maximal link distance linkdistance real Largest distance in pixels that objects may move between frames
Fusion allowed fusion boolean
No of frames that an object can skip skipframes integer If no objects are found in the next frame to link an object (within maximal link distance radius), further n frames will be looked. Set 0 to not to allow frame skipping.
Weight for isolation sigmaiso real Weight applied to isolated objects.
Weight distance sigmac real Weight factor for the distance that objects moved between frames
Weight size difference sigmaa real Penalizes the square of pixel area differences.
Weight shape difference sigmash real Penalizes the square of shape factor difference.
Weight mean intensity diff 1 sigmai1 real Weight factor for difference in intensities of objects in image B
Weight sum intensity diff 1 sigmacc1 real Weight factor for difference in intensities of objects in image B
Weight mean intensity diff 2 sigmai2 real Weight factor for difference in intensities of objects in image B
Weight sum intensity diff 2 sigmacc2 real Weight factor for difference in intensities of objects in image B
Weight mean intensity diff 3 sigmai3 real Weight factor for difference in intensities of objects in image B
Weight sum intensity diff 3 sigmacc3 real Weight factor for difference in intensities of objects in image B
Remove segments represented less than removeseg integer Removes segments that are only present in the given number of frames
Starting Temperature tstart real Area in pixels of objects typically differ between frames
Temperature divisor tdiv real Area in pixels of objects typically differ between frames
Textual Output textoutput boolean Shows segmentation results in text window.
Annotate Image annotate boolean Adds annotation to the tracked image.
Description:
Tracks segments of a segmented image (A) from frame to frame. Additional intensity information in images (B) are used to distinguish segments.
Image A has to be segmented first with the Simple or Watershed Segmentation functions. These segmentation functions segment each frame independently. Tracking will find the instances of the same object in the successive time frames, and mark them as the same segment. The result is a series of modified segmented images where the markers (the values associated with pixels) refer to the same tracked segment throughout the time lapse.
Algorithm: The only available algorithm is Simulated Annealing.
The algorithm randomly changes connections between segments in consecutive frames seeking for the best matching in the vicinity given by the "Maximal link distance". The best match is determined by energy minimization: the squared distance (square of the difference) of: the distance of the center and the size of the segment; and the mean and sum intensities of the associated images (Image Bs) are calculated and normalized by the mean minimal squared distance of these qualities, multiplied by the "Weight factors". The energy of a disconnected segment is 1 for each quality.
To track fusion and fission(division) events - or more often segmentation artifacts - segments can be linked to group of segments. Within "Group size diameter" distance segments can form a group of two if their total area is less then "Maximal group area" and the normalized squared distance of intensities is less than "Group max energy". Grouping is then recursed by "Group recursion" times yielding more complex groups.
Tracking is performed randomly changing connections between segments favoring lower energy states. Initially "thermal noise" is introduced given by the "Starting Temperature" and then it is exponentially decreased by "Temperature divisor" resulting "freezing" of the system in a low energy state.
Segments finally tracked along the optimized links. "Fusion allowed" tracking backwards, thus spatially distant objects that fuse later on will be identified as the same object.
Segments that are represented in less than "Remove segments represented less than" frames are completely removed.
The algorithm is a modification of the tracking algorithm published by Racine et al. Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on Volume , Issue , 6-9 April 2006 Page(s):1020 - 1023.
Hints:
Up to 3 different intensity images can be associated. These can be processed images which can provide texture information e.g. by using high pass filtering, or motion information by using Optical Flow images.
Wider grouping criteria can drastically increase memory requirement and computation time.