`Statistical_Relaxation''---Relaxation labeling using manually-set statistics of image regions

purpose:

Uses relaxation labeling to segment an image into 2-4 distinct regions. The algorithms to compute the initial probability vectors, perform the updating, and compute a final segmentation can be found in [7] and [8]. Briefly, using the naming as is found in [8], the strategies used for this version of relaxation labeling are: initial probabilities--- Basic, vector updating--- fast general using support-reject compatibility coefficients. For final classification, each voxel gets the label corresponding to the largest vector component in that voxel's probability vector, provided it exceeds ``final segmentation threshold.''

Region parameters Mean and Standard Deviation are manually set by user as opposed to Cue-based_Relaxation_Labeling where region parameters are computed from cues.

input:

An 8-bit gray scale volume.

output:

An 8-bit volume in segmentation volume format (refer to the Demask_Region function, p. ) containing the segmented regions.

parameters:

Default parameters menu is

number of regions to segment = 2
* Region 1 parameters:
* Mean: 192
* Standard Deviation:10
* Region 2 parameters:
* Mean: 128
* Standard Deviation:10
* Region 3 parameters:
* Mean: 0
* Standard Deviation:0
* Region 4 parameters:
* Mean: 0
* Standard Deviation:0
* Number of updating iterations = 10
* input from vol# = 0
* final segmentation threshold = 0.000
*

If the final segmentation threshold is set to 0.0, then the maximum vector component for each voxel is assumed to represent that voxel's appropriate labeling. If a threshold is set, then the maximum vector component value for a voxel must be greater than the threshold value for that voxel to be labeled as part of a region.

comments:

 

1. This ``turnkey'' version of the relaxation labeling function is described in detail in [8].
2. Function works identically to Cue-based_Relaxation_Labeling, except that region parameters Mean and Standard Deviation are set manually.