

Name  Biomat 
Software  ImageJ 
Author  Jiří Janáček 
Maintainer  
Source  
Status 
Plugins for 3D image preprocessing.
Stack Linear Contrast  multiplies images in stack by coefficient obtained by linear interpolation of the “first” and “last” coefficient. A simple tool for compensation of contrast decreasing with depth within thick sample.
Lipschitz 3D Filter  top hat  subtracts slowly varying background calculated as lower Lipschitz envelope from the image.
Preprocessing example: Image of capillaries in brain
 Plugins › Biomat › Stack Linear Contrast with parameters (multiplyers) “first”= 1.0 and “last”= 3.0
 Process › Filters › Gaussian blur 3D with “sigma”= 1 pixel
 Plugins › Biomat › Lipschitz 3D Filter with parameter “slope”= 2 / pixel
Plugins for detection of fibres in 3D image.
Tensor Line 3D Filter  enhances white fibers of uniform width sparsely distributed on dark background.
Example: Image of capillaries in adipose tissue.
 Plugins › Biomat › Tensor Line 3D Filter with “sigma” set to 3 pixels

Image › Adjust › Brightness/Contrast
 Process › Filters › Gaussian blur 3D with “sigma”= 1 pixel
Vector Line 3D Filter  enhances white fibers of varying thickness. Crossection of the fibers need not be circular. Parameter “sigma” in pixels corresponds to the largest diameter.
Example: Image of capillaries in embryonic heart.
 Plugins › Biomat › Vector Line 3D Filter with parameters “sigma”= 4 pixels, “scale number”= 2
Plugins for evaluation of 2D images using heat equation.
2D Tensor Color Coding  standard color coding of 2D tensor image. Symmetric tensor is coded as channels of 32 bit image stacks.
2D Heat Kernel Tensor  second order moments of heat kernel calculated from 8 bit binary image.
2D Tensor Statistics  summary of tensor image (in ROI). “Value” is average trace of the tensor, “shape” is the ratio of its eigenvalues and “angle” of the first eigenvector is measured counterclockwise from the horizontal axis.