Difference between revisions of "Medical Imaging Example Meshes"
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* Adaptive with Min-Edge = 15: 67,920 triangles | * Adaptive with Min-Edge = 15: 67,920 triangles | ||
− | [[File:COVID-19-23354,uniform,e=15,suface | + | [[File:COVID-19-23354,uniform,e=15,suface.png|500px|COVID-19-23354,uniform,e=15,suface.png]] |
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<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
+ | 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 | ||
</gallery> | </gallery> | ||
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
+ | 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,zoom.png | ||
</gallery> | </gallery> | ||
Revision as of 16:01, 14 March 2020
Contents
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,triangulation
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
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
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
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
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
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