Difference between revisions of "Medical Imaging Example Meshes"

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(→‎COVID-19-23354)
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* Adaptive with Min-Edge = 15: 67,920 triangles
 
* Adaptive with Min-Edge = 15: 67,920 triangles
  
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[[File:COVID-19-23354,uniform,e=15,suface.png|500px|COVID-19-23354,uniform,e=15,suface.png]]
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File:COVID-19-23354,uniform,e=15,suface.png
 
File:COVID-19-23354,uniform,e=15,suface.png
 
File:COVID-19-23354,uniform,e=15,triangulation.png
 
File:COVID-19-23354,uniform,e=15,triangulation.png
 
File:COVID-19-23354,uniform,e=15,triangulation,zoom.png
 
File:COVID-19-23354,uniform,e=15,triangulation,zoom.png
 
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File:COVID-19-23354,w=0.1,e=15,suface.png
 
File:COVID-19-23354,w=0.1,e=15,suface.png
 
File:COVID-19-23354,w=0.1,e=15,triangulation.png
 
File:COVID-19-23354,w=0.1,e=15,triangulation.png

Revision as of 16:02, 14 March 2020

2D Example Meshes

The directory containing the 2D input data is located in the 2D folder of Medical_Imaging_Data.

The image data were acquired from Centers for Disease Control and Prevention

COVID-19-23354

  • Input image : Dimensions (3000x2000) with spacing (1x1)
  • Uniform with Min-Edge = 15: 82,981 triangles
  • Adaptive with Min-Edge = 15: 67,920 triangles
  • COVID-19-23354,uniform,e=15,suface.png
  • COVID-19-23354,uniform,e=15,triangulation.png
  • COVID-19-23354,uniform,e=15,triangulation,zoom.png
  • COVID-19-23354,w=0.1,e=15,suface.png
  • COVID-19-23354,w=0.1,e=15,triangulation.png
  • COVID-19-23354,w=0.1,e=15,triangulation,zoom.png

Commands to generate meshes :

Uniform with Min-Edge = 15 : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./Medical_Imaging_Data/2D/COVID-19-23354.tif --uniform --min-edge 15 --output ./COVID-19-23354,uniform,e=15.vtk

Adaptive with Min-Edge = 15 : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./Medical_Imaging_Data/2D/COVID-19-23354.tif --min-edge 15 --output ./COVID-19-23354,w=0.1,e=15.vtk

COVID-19-23311

  • Input image : Dimensions (255x255x229) with spacing (0.976562x0.976562x1.40002)
  • Uniform with Delta = default: 205,416 tetrahedra
  • Uniform with Delta = 1.5: 770,853 tetrahedra
  • Head-Neck,d=2.49023.png
  • Head-Neck,d=2.49023,zoom.png
  • Head-Neck,d=1.5.png
  • Head-Neck,d=1.5,zoom.png

Commands to generate meshes :

Uniform with Delta = default : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --output ./Head-Neck,d=2.49023.vtk

Uniform with Delta = 1.5 : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --delta 1.5 --output ./Head-Neck,d=1.5.vtk

3D Example Meshes

The directory containing the 3D input data is located in the 3D folder of Medical_Imaging_Data.

Head-Neck

  • Input image : Dimensions (255x255x229) with spacing (0.976562x0.976562x1.40002)
  • Uniform with Delta = default: 205,416 tetrahedra
  • Uniform with Delta = 1.5: 770,853 tetrahedra
  • Head-Neck,d=2.49023.png
  • Head-Neck,d=2.49023,zoom.png
  • Head-Neck,d=1.5.png
  • Head-Neck,d=1.5,zoom.png

Commands to generate meshes :

Uniform with Delta = default : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --output ./Head-Neck,d=2.49023.vtk

Uniform with Delta = 1.5 : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --delta 1.5 --output ./Head-Neck,d=1.5.vtk

Brain-With-Tumor-Case17

  • Input image : Dimensions (448x512x176) with spacing (0.488281x0.488281x1)
  • Uniform with Delta = default: 222,540 tetrahedra
  • Graded with Delta = default: 94,383 tetrahedra
  • Brain-With-Tumor-Case17,d=1.76001.png
  • Brain-With-Tumor-Case17,d=1.76001,zoom.png
  • Brain-With-Tumor-Case17,d=1.76001,graded.png
  • Brain-With-Tumor-Case17,d=1.76001,graded,zoom.png

Commands to generate meshes :

Uniform with Delta = default : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Brain-With-Tumor-Case17.nii --output ./Brain-With-Tumor-Case17,d=1.76001.vtk

Graded with Delta = default : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Brain-With-Tumor-Case17.nii --volume-grading --output ./Brain-With-Tumor-Case17,d=1.76001,graded.vtk

Knee-Char

  • Input image : Dimensions (512x512x119) with spacing (0.27734x0.27734x1)
  • Uniform with Delta = default case: 386,869 tetrahedra
  • Graded with Delta = default case: 274,309 tetrahedra
  • Knee-Char,d=1.19.png
  • Knee-Char,d=1.19,zoom.png
  • Knee-Char,d=1.19,graded.png
  • Knee-Char,d=1.19,graded,zoom.png

Commands to generate meshes :

Uniform with Delta = default : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --output ./Knee-Char,d=1.19.vtk

Graded with Delta = default : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --volume-grading --output ./Knee-Char,d=1.19,graded.vtk

Ircad2

  • Input image : Dimensions (512x512x219) with spacing (0.976562x0.976562x1.40002)
  • Uniform with Delta = 2 case: 5,031,442 tetrahedra
  • Graded with Delta = 1 case: 6,072,751 tetrahedra
  • Ircad2,d=2.png
  • Ircad2,d=2,zoom.png
  • Ircad2,d=1,graded.png
  • Ircad2,d=1,graded,zoom.png

Commands to generate meshes :

Uniform with Delta = 2 : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Ircad2.nrrd --delta 2 --output ./Ircad2,d=2.vtk

Graded with Delta = 1 : Output Mesh 

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Ircad2.nrrd --delta 1 --volume-grading --output ./Ircad2,d=1,graded.vtk
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