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Biomat

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Plugins for 3D image preprocessing

Stack Linear Contrast - multiplies images in stack by coefficient obtained by linear interpolation of the “first” and “last” parameter. 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: Stack of confocal microscopy images of capillaries in rat brain

https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/capillaries_brain_3Dg.gif

Original data

  • PluginsBiomatStack Linear Contrast with “first” = 1.0 and “last” = 3.0
  • ProcessFiltersGaussian blur 3D with “sigma” = 1 pixel
  • PluginsBiomatLipschitz 3D Filter with “slope” = 2 and “top hat” on
https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/capillaries_brain_proc_3Dg.gif

Processed data

Plugins for detection of fibres in 3D image

Tensor Line 3D Filter - enhances white fibers of uniform width sparsely distributed on dark background.

Example: Stack of confocal microscopy images of capillaries in adipose tissue.

https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/capillaries_adipose_3Dg.gif

Original data

  • PluginsBiomatTensor Line 3D Filter with “sigma” = 3 pixels
  • ImageAdjustBrightness/Contrast
  • ProcessFiltersGaussian blur 3D with “sigma” = 1 pixel
https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/capillaries_adipose_proc_3Dg.gif

Processed data

Vector Line 3D Filter - enhances white fibers of varying width. Crossection of the fibers need not be circular. Parameter “sigma” in pixels corresponds to the largest diameter.

https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/cardio,3-18_sp.2_rec0.5mov.gif

Original data

https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/cardio,3-18_sp.2_rec0.5_4_2_3_v3dlin_mov.gif

Processed data

Example: Stack of MicroCT images of capillaries in rodent embryonic heart.

  • PluginsBiomatVector Line 3D Filter with “sigma” = 4 pixels and “scale number” = 2

Plugins for evaluation of directionality in 2D images using heat equation

2D Heat Kernel Tensor - second order moments of heat kernel calculated from 8 bit binary image.

2D Tensor Color Coding - standard color coding of 2D tensor image. Symmetric tensor is coded as channels of 32 bit image stacks.

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.

Example: Projection of binary images of capillaries in brain.

https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/MAX_2_4cortexa1.png

Binary image

  • PluginsBiomat2D Heat Kernel Tensor
  • PluginsBiomat2D Tensor Statistics
https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/MAX_2_4cortexa1_res.png

Statistics

  • ProcessBiomat2D Tensor Color Coding
https://raw.githubusercontent.com/jiri-janacek/biomat/b9b53126134ac7e9fbca9a29de66bc7f2b7c845e/media/MAX_2_4cortexa1_tens_col.png

Color coded tensor image