Difference between revisions of "3D Reslicing using COMKAT image tool (basic)"

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Set up coordinate transform for desired slice
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Specify the transformation matrix based on desired pixel spacing (zoom), position (location), orientation. ref [http://medical.nema.org/dicom/2004/04_03PU.PDF] p. 275
User specifies this based on desired pixel spacing (aka zoom), position (location), orientation. ref [http://medical.nema.org/dicom/2004/04_03PU.PDF] p 275
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   M = ( Insert the method for generate the transformation );
 
   M = ( Insert the method for generate the transformation );
 
  
  
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this documents physical location voxels in the volume
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Specify the reverse mapping matrix ( xyz --> index space of the original image volume )
Specify the reverse mapping matrix from xyz --> index space of the original image volume
 
  
 
   Mhat = ( Insert the method for generate the mapping);
 
   Mhat = ( Insert the method for generate the mapping);
  
  
Calculate voxe indcies into the volume corresponding to xyz physical location
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Calculate voxel indcies into the volume corresponding to xyz physical location
  
 
   uvw =  Mhat * xyz;
 
   uvw =  Mhat * xyz;

Revision as of 23:16, 7 August 2012

Reslicing 3D image volume using COMKAT image tool (basic)

Overview

Reslicing a 3D (or 3D vs time) image dataset can be accomplished using the COMKAT image tool and sliceVolume(). This example explains how to create image slices from a volume in at a position, plane orientation, and magnification. The approach is to load the image volume dataset into an instance if an ImageVolumeData (abbreviated IVD) object and to use the sliceVolume() method.

Background

sliceVolume() is a mex-file written in c with an interface to MATLAB that makes the operation particularly efficient. COMKATImageTool uses sliceVolume() and you can use it too.


Approach I. Demonstrates coordinate transformations

Load a file using COMKAT image tool and use the functions to translate and rotate the image volume as you desire.

  ivd = ImageVolumeData();


Use read data to ivd, e.g. read_DICOM()

  ivd = read_DICOM(ivd, pathName, fileName); % load volume into an instance of IVD object;


Create a list of indicies of all pixels in slice that we are creating

  [i, j] = meshgrid(0 : Nc-1, 0 : Nr-1);
   ij = [c(:)’ ; r(:)’];  % make matrix, each column corresponding to a single pixel in the slice we are creating


Specify the transformation matrix based on desired pixel spacing (zoom), position (location), orientation. ref [1] p. 275

  M = ( Insert the method for generate the transformation );


Calculate physical (mm) location of each pixel in the desired slice

  xyz = M * ij;


Specify the reverse mapping matrix ( xyz --> index space of the original image volume )

  Mhat = ( Insert the method for generate the mapping);


Calculate voxel indcies into the volume corresponding to xyz physical location

  uvw =  Mhat * xyz;


Use sliceVolume() to interpolate the results

  slice = sliceVolume(idv, v, u, w, backgroundPixelValue, ‘linear);


Display new slice

  figure, imagesc(slice); axis image % isotropic

Approach II. Uses coordinateGen to do the coordinate transformation)

this should create same result as approach 1 but require fewer lines of coding since coordinateGen does most things that are needed


Read the image volume into an ImageVolumeData object

  ivd = ( Insert the method for reading data );

Use coordinateGen() to generate uvw

  [u, v, w] = coordinateGen(ivd, Nc, Nr, pixelSpacing, planePos, orientationInput);


Use sliceVolume() to interpolate

  slice = sliceVolume(idv, v, u, w, backgroundPixelValue, ‘linear);


Display slice

  figure, imagesc(slice); axis image % isotropic