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

Watershed Segmentation ( IAAdvSegment )

Parameters:

Name	Short Name	Type	Description
Threshold value calculation method	type	string	How is the threshold level calculated: "Pixel value", "Percentile by frames", "Percentile by series", "Percentile by reference", "Otsu by frames", "Otsu by series", "Otsu by reference"
Way	way	string	"Above" for bright objects or "Below" for dark objects.
Value	value	real	Pixel value, percentile, or factor times Otsu optimal threshold value (typically 1)
Threshold from local max/min	proctype	string	"Bound uniformly" and "Bound locally" enables local maximum or minimum search. Set None for global thresholding.
Determine boundaries at	value2	real	For "Bound locally", the boundary of each object is determined at this % of the maximal intensity of the object relative to its neighborhood. For "Bound uniformly" this is a pixel intensity value.
Method	method	string	The method of separating objects from each other: "Mark Seed", "Mark Shape", "Watershed(que)", "Watershed(distance)", "Gradient".
Connectivity	connectivity	string	How the objects are propagated from the seeds: "Inf (3x3 rectangular)", "L4 (3x3 cross)", "L2", "Fast Marching"
Separate segments	separate	boolean	If yes segments will not touch each other.
Weld segments into round objects	weld	boolean	Weld touching segments if they form a rounder object together. Use this to avoid objects fragmenting into multiple segments.
Evaluate segment data	evaluate	boolean	If yes measures segments and applies classifiers, if no only marks segments with different values.
Data/Text Window Output	textoutput	boolean	Whether to show segmentation results data in a text or Excel Data window. If "No" the segment data are still available for plotting.
Keep original mask	keeporigmask	boolean	Originally masked areas are kept masked if Yes. Otherwise the mask will take zero, ceiling or bottom value.
Discard segments at edges	noedges	boolean	Any segment that has at least 10% of its boundary at the edge of the image will be discarded.

Description:

Watershed Segmentation (formerly Advanced Segmentation). Segments grayscale images using the Watershed algorithm. The threshold value calculation methods are identical to the ones used for the Threshold function.
Way: Above segments bright details, Below segments dark details as objects
Segmentation is performed from local maxima or minima for "Above" or "Below" setting, respectively at the "Way" parameter.
Threshold from local max/min: "None" calculates simple threshold according to the threshold value, "Bound uniformly" calculates segment boundary with morphological reconstruction using a cap value modified by the "Determine boundaries at" value. Bound locally will bound local maxima at their given percent compared to the minimum or maximum of the image. This is performed by flood filling from the local maximum or minimum, respecting the boundaries of the Watershed segments.
Determine boundaries at: when "Bound uniformly" is selected above, given in the same units and additive to the threshold value, and sets how far from the local maximum will the boundary of the object drawn. When "Bound locally" is selected, it is a value in percents of local maximum or minimum.
Method: "Mark Seed" shows local maxima or minima by each as a single pixel. "Mark Shape" shows the boundaries of the objects, undivided by the watershed algorithm. Watershed divides bounded segments propagating from local maxima or minima.
The number of segments is limited only by the available memory.
Note: the segmentation algorithm has integer core, and does not work properly if the image consist of small, fractional values. Use Scalar Arithmetic to set a proper range, where pixel values are >>1.
The "Keep original mask" is not applicable here; masked areas are ignored during threshold calculation, but substituted by zeros in the segmented images.