Difference between revisions of "Medical Imaging Example Meshes"

From crtc.cs.odu.edu
Jump to: navigation, search
(COVID-19-23354)
(2D Example Meshes)
Line 2: Line 2:
 
=2D Example Meshes=
 
=2D Example Meshes=
 
The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/wd0i18giti2zo330y19xhkqu8wjzgf7j Medical_Imaging_Data].
 
The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/wd0i18giti2zo330y19xhkqu8wjzgf7j Medical_Imaging_Data].
 
The image data were acquired from [https://www.cdc.gov/media/subtopic/images.htm Centers for Disease Control and Prevention]
 
  
 
==COVID-19-23354==
 
==COVID-19-23354==

Revision as of 19:46, 14 March 2020

2D Example Meshes

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

COVID-19-23354

  • Input image : Dimensions (3,000x2,000) with spacing (1x1)
  • Uniform with Min-Edge = 15: 82,981 triangles
  • Adaptive with Min-Edge = 15: 67,920 triangles

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

Mesh generated based on the images published at Centers for Disease Control and Prevention. For the uniform meshes, the edge-size corresponds to 15 pixels. The adaptive meshes were created by controlling the size of the elements based on the difference in the intensity of the pixels.

COVID-19-23311

  • Input image : Dimensions (2,460x2,460) with spacing (1x1)
  • Uniform with Min-Edge = 20: 47,028 triangles
  • Adaptive with Min-Edge = 20: 34,080 tetrahedra

Commands to generate meshes :

Uniform with Min-Edge = 20 : Output Mesh

docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./Medical_Imaging_Data/2D/COVID-19-23311.tif --uniform --min-edge 20 --output ./COVID-19-23311,uniform,e=20.vtk

Adaptive with Min-Edge = 20 : Output Mesh

docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./Medical_Imaging_Data/2D/COVID-19-23311.tif --min-edge 20 --output ./COVID-19-23311,w=0.1,e=20.vtk

Mesh generated based on the images published at Centers for Disease Control and Prevention. For the uniform meshes, the edge-size corresponds to 20 pixels. The adaptive meshes were created by controlling the size of the elements based on the difference in the intensity of the pixels.

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 --threads 4 --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 --threads 4 --volume-grading --output ./Ircad2,d=1,graded.vtk