03. volume - intra volume propagative slice registration

This process can be used after the histological slices have been stacked in the direction orthogonal to the cut-plane, by running one of the two following processes: Stacking individual slices or Individualizing and Stacking multiple slices. It enables you to align 2D histological slices into a 3D anatomical volume using the block-matching registration method (Ourselin et al, 2001) in a propagative scheme.

The anatomical volume is reconstructed by registering each histological slice with the following one in the stack. Then, by composition of the previously assessed transformations, each slice is aligned to a reference slice so as to obtain a consistent 3D anatomical volume. The reference slice has to be selected because it carries few artefacts such as folds or tears and can be located in the middle of the volume to limit error propagation.

Parameters

Input_3dImage: 3D Volume ( input )

Click on .
Select the initial reconstructed volume you have obtained by stacking the individualized coronal histological slices in the direction orthogonal to the cut-plane (output file from the process Stacking individual slice or Individualizing and stacking multiple slices), for instance Test_volume_rat1_cresyl.ima

Reference_Slice_Number: Integer ( input )

Enter the number of the slice chosen as reference.
A default value is automatically assigned according to the total number of sections in the volume to be reconstructed. This is the result of the following calculation:
ceil( Total number of slices / 2 ) - 1.

There are 162 slices in Test_volume_rat1_cresyl.ima, its corresponding Reference_Slice_Number value is hence 80.

Channel: Choice ( input )

Transformation: Choice ( input )

Select transformation type to estimate :

• rigid => estimates translation and rotation parameters
• similitude => estimates translation, rotation and scaling parameters
• affine => estimates translation, rotation, scaling and shearing parameters

High_Threshold: Integer ( optional, input )

Start_Level: Integer ( optional, input )

Registration between slices are estimated using multiresolution algorithms. Enter the number at which the multiresolution pyramid starts.

Stop_Level: Integer ( optional, input )

Registration between slices are estimated using multiresolution algorithms. Enter the number at which the multiresolution pyramid stops.

Init_Transfo_Reference: Choice ( optional, input )

Select the type of initialization used for registration between slices.

• No => do not initialize registration using gravity center estimation
• Low => initialize registration using gravity center of images. Use this value if images have light color background.
• High => initialize registration using gravity center of images. Use this value if images have dark color background.

Percent_Kept: Float ( optional, input )

Enter the percent of image blocks kept to estimate registration between slices.

Output_3dImage: 3D Volume ( output )

Click on .
Specify the output directory and enter the output file name, for instance Test_volume_rat1_cresyl_aligned.ima

NOTE: Name choice is important to identify the content of an image and distinguish it of each other.

Technical information

Toolbox : BrainRAT

User level : 0

Identifier : IntraVolumePropagativeSliceRegistration

File name : brainvisa/toolboxes/brainrat/processes/2d-3dpmi/IntraVolumePropagativeSliceRegistration.py

Supported file formats :

Input_3dImage :

GIS image, TIFF image, TIFF(.tif) image, JPEG image

Output_3dImage :

GIS image, TIFF image, TIFF(.tif) image, JPEG image