Computer Vision News - November 2020

6 This should return the following, showing the basic instructions on how to use reg_ tools. A basic application could be to use reg_tools to mask two images, and then apply a registration on the output of the masking. The following snippet of code can be used for this: Registration Tool Comparison reg_tools -in ~/Desktop/myProject/DATA/mr_image.nii -out ~/Desktop/myProject/DATA/mr_image_nan.nii -nan ~/Desktop/myProject/DATA/mask.nii reg_tools -in ~/Desktop/myProject/DATA/ct_image.nii -out ~/Desktop/myProject/DATA/ct_image_nan.nii -nan ~/Desktop/myProject/DATA/mask.nii reg_aladin -ref ~/Desktop/myProject/DATA/mr_image_nan.nii -flo ~/Desktop/myProject/DATA/ct_image_nan.nii You should keep in mind that the output of the registration will be automatically saved as nifti image in the niftyreg folder by default, but you can change this using the argument -res <filename>. Eidolon: a complex framework for visualization of medical images and a focus on cardiac data Eidolon is a more recent tool than the previous ones, implemented in Python and open to customization. At its current stage, it already represents a very powerful and comprehensive biomedical visualization and analysis framework. Usage: reg_tools -in <filename> -out <filename> [OPTIONS]. -in <filename> Filename of the input image image (mandatory) * * OPTIONS * * -out <filename> Filename out the output image [output.nii] -add <filename/float> This image (or value) is added to the input -sub <filename/float> This image (or value) is subtracted to the input -mul <filename/float> This image (or value) is multiplied to the input -div <filename/float> This image (or value) is divided to the input -smo <float> The input image is smoothed using a b-spline curve -smoG <float> <float> <float> The input image is smoothed using Gaussian kernel -rms <filename> Compute the mean rms between both image -bin Binarise the input image (val!=0?val=1:val=0) -thr <float> Thresold the input image (val<thr?val=0:val=1) -nan <filename> This image is used to mask the input image. Voxels outside of the mask are set to nan