|
|
| Line 3: |
Line 3: |
| | =3D Example Meshes= | | =3D Example Meshes= |
| | The directory containing the 3D input data is located in the 3D folder of [https://odu.box.com/s/olefferrnksu2nmerbfvbvsz2u4abbdw Medical_Imaging_Data]. | | The directory containing the 3D input data is located in the 3D folder of [https://odu.box.com/s/olefferrnksu2nmerbfvbvsz2u4abbdw Medical_Imaging_Data]. |
| − |
| |
| − | ==COVID-19-Main-Protease-6y2e==
| |
| − | * [https://odu.box.com/s/eb9s3vrvml0gop7mdpwckh6xnn27eiut Input Image]
| |
| − | * Input image : Dimensions (284x303x344) with spacing (0.2226907x0.2226907x0.2226907)
| |
| − | * Uniform with Delta = 0.3: 2,509,202 tetrahedra
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-Main-Protease-6y2e,d=0.5.png
| |
| − | File:COVID-19-Main-Protease-6y2e,d=0.5,clip.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-Main-Protease-6y2e,d=0.5,label=1.png
| |
| − | File:COVID-19-Main-Protease-6y2e,d=0.5,label=2.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Delta = 0.3:''' [https://odu.box.com/s/jeks38sn5slw38gbit6t0rf25fzv6jpb Output Mesh]
| |
| − | <pre>
| |
| − | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/COVID-19-Main-Protease-6y2e.nrrd --delta 0.3 --output ./COVID-19-Main-Protease-6y2e,d=0.3.vtk
| |
| − | </pre>
| |
| − |
| |
| − | Uniform tetrahedral mesh capable to help identify the internal voids of the <b>COVID-19 Main Protease. </b> Biological assembly data was retrieved from the molecule [https://www.rcsb.org/structure/6y2e 6y2e], [https://www.rcsb.org/ Protein Data Bank].
| |
| − |
| |
| − | ==COVID-19-NSP-15-Endoribonuclease-6vww==
| |
| − | * [Input Image]
| |
| − | * Input image : Dimensions (303x297x337) with spacing (0.3445713x0.3445713x0.3445713)
| |
| − | * Uniform with Delta = 0.5: 2,310,215 tetrahedra
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-NSP-15-Endoribonuclease-6vww,d=0.3.png
| |
| − | File:COVID-19-NSP-15-Endoribonuclease-6vww,d=0.3,clip.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-NSP-15-Endoribonuclease-6vww,d=0.3,label=1.png
| |
| − | File:COVID-19-NSP-15-Endoribonuclease-6vww,d=0.3,label=2.png
| |
| − | File:COVID-19-NSP-15-Endoribonuclease-6vww,d=0.3,label=3.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Delta = 0.5:''' [https://odu.box.com/s/tkk8f8o1tctf52bop07a6hxy87ugt8kg Output Mesh]
| |
| − | <pre>
| |
| − | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/COVID-19-NSP-15-Endoribonuclease-6vww.nrrd --delta 0.5 --output ./COVID-19-NSP-15-Endoribonuclease-6vww,d=0.5.vtk
| |
| − | </pre>
| |
| − |
| |
| − | Uniform tetrahedral mesh capable to help identify the internal voids of the <b>COVID-19 NSP15 Endoribonuclease. </b> Biological assembly data was retrieved from the molecule [https://www.rcsb.org/structure/6vww 6vww], [https://www.rcsb.org/ Protein Data Bank].
| |
| − |
| |
| − | ==COVID-19-Spike-Glycoprotein-6vxx==
| |
| − | * [https://odu.box.com/s/jt2z4vqq3vs8211uuah7m2qfnyk1tjq8 Input Image]
| |
| − | * Input image : Dimensions (281x380x302) with spacing (0.427871x0.427871x0.427871)
| |
| − | * Uniform with Delta = 0.5: 3,260,055 tetrahedra
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-Spike-Glycoprotein-6vxx,d=5.png
| |
| − | File:COVID-19-Spike-Glycoprotein-6vxx,d=5,zoom.png
| |
| − | </gallery>
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-Spike-Glycoprotein-6vxx,d=5,label=1.png
| |
| − | File:COVID-19-Spike-Glycoprotein-6vxx,d=5,label=2.png
| |
| − | File:COVID-19-Spike-Glycoprotein-6vxx,d=5,label=3.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Delta = 0.5:''' [https://odu.box.com/s/0s3zxk3t2hsvmt43l4i9pabm602tiqbk Output Mesh]
| |
| − | <pre>
| |
| − | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/COVID-19-Spike-Glycoprotein-6vxx.nrrd --delta 0.5 --output ./COVID-19-Spike-Glycoprotein-6vxx,d=5.vtk
| |
| − | </pre>
| |
| − |
| |
| − | Uniform tetrahedral mesh capable to help identify the internal voids of the <b>COVID-19 spike glycoprotein. </b> Biological assembly data was retrieved from the molecule [https://www.rcsb.org/structure/6vxx 6vxx], [https://www.rcsb.org/ Protein Data Bank].
| |
| − |
| |
| − | ==COVID-19-Spike-Glycoprotein-6vsb==
| |
| − | * [https://odu.box.com/s/hebeasclyuekcavgvftb9vbsirrbqj7t Input Image]
| |
| − | * Input image : Dimensions (220x223x314) with spacing (0.551042x0.551042x0.551042)
| |
| − | * Uniform with Delta = 0.4: 5,731,833 tetrahedra
| |
| − | * Graded with Delta = 0.4: 3,794,223 tetrahedra
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-Spike-Glycoprotein-6vsb,d=0.4.png
| |
| − | File:COVID-19-Spike-Glycoprotein-6vsb,d=0.4,clip.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-Spike-Glycoprotein-6vsb,d=0.4,graded.png
| |
| − | File:COVID-19-Spike-Glycoprotein-6vsb,d=0.4,graded,clip.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Delta = 0.4:''' [https://odu.box.com/s/wth64bzfotibrwv3t25kn2oyzo0dqntm Output Mesh]
| |
| − | <pre>
| |
| − | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/COVID-19-Spike-Glycoprotein-6vsb.nrrd --delta 0.4 --output ./COVID-19-Spike-Glycoprotein-6vsb,d=0.4.vtk
| |
| − | </pre>
| |
| − |
| |
| − | '''Graded with Delta = 0.4:''' [https://odu.box.com/s/2kn1ovwpa6jarj8wssmeqz2y5zc19fc2 Output Mesh]
| |
| − | <pre>
| |
| − | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/COVID-19-Spike-Glycoprotein-6vsb.nrrd --delta 0.4 --volume-grading --output ./COVID-19-Spike-Glycoprotein-6vsb,d=0.4,graded.vtk
| |
| − | </pre>
| |
| − |
| |
| − | Uniform and graded tetrahedral meshes capable to help identify the internal voids of the <b>COVID-19 spike glycoprotein. </b> The middle and right meshes are slices. Biological assembly data was retrieved from the molecule [https://www.rcsb.org/structure/6vxx 6vxx], [https://www.rcsb.org/ Protein Data Bank].
| |
| − |
| |
| − | ==Brain-With-Tumor-Case17==
| |
| − | * [https://odu.box.com/s/ynudkxeozt5j82v1qmoovif10c73taw7 Input Image]
| |
| − | * Input image : Dimensions (448x512x176) with spacing (0.488281x0.488281x1)
| |
| − | * Uniform with Delta = default: 222,540 tetrahedra
| |
| − | * Graded with Delta = default: 94,383 tetrahedra
| |
| − |
| |
| − | <gallery mode="packed" heights=350px>
| |
| − | File:Brain-With-Tumor-Case17,d=1.76001.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=350px>
| |
| − | File:Brain-With-Tumor-Case17,d=1.76001,graded.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Delta = default:''' [https://odu.box.com/s/5dqgw5pykve4xv2ii30xnkjq5s3maxdl Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| − |
| |
| − | '''Graded with Delta = default:''' [https://odu.box.com/s/8zlfyepfuzmd8g119eup5n2srxpbqg8s Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| − |
| |
| − | ==Head-Neck==
| |
| − | * [https://odu.box.com/s/zj492g475bo93kyrd1npmisy2gwdqorj Input Image]
| |
| − | * Input image : Dimensions (255x255x229) with spacing (0.976562x0.976562x1.40002)
| |
| − | * Uniform with Delta = default: 205,510 tetrahedra
| |
| − | * Uniform with Delta = 1.5: 767,393 tetrahedra
| |
| − |
| |
| − | <gallery mode="packed" heights=350px>
| |
| − | File:Head-Neck,d=2.49023.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=350px>
| |
| − | File:Head-Neck,d=1.5.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Delta = default:''' [https://odu.box.com/s/zoi0em9twv0mgt2d1244yujtkd3nit3e Output Mesh]
| |
| − | <pre>
| |
| − | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Head-Neck.mha --output ./Head-Neck,d=2.49023.vtk
| |
| − | </pre>
| |
| − |
| |
| − | '''Uniform with Delta = 1.5:''' [https://odu.box.com/s/jo4cwfrn1bvslocv9b11m0i9dhxyvdrc Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| | | | |
| | ==Ircad2== | | ==Ircad2== |
| Line 213: |
Line 62: |
| | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Knee-Char.mha --volume-grading --output ./Knee-Char,d=1.19,graded.vtk | | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./Medical_Imaging_Data/3D/Knee-Char.mha --volume-grading --output ./Knee-Char,d=1.19,graded.vtk |
| | </pre> | | </pre> |
| − |
| |
| − | =2D Example Meshes=
| |
| − | The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/olefferrnksu2nmerbfvbvsz2u4abbdw Medical_Imaging_Data].
| |
| − |
| |
| − | ==COVID-19-23311==
| |
| − | * [https://odu.box.com/s/musv3zdpx6a76p282t2xn905rf0xlwty Input Image]
| |
| − | * 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
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-23311,uniform,e=20,suface.png
| |
| − | File:COVID-19-23311,uniform,e=20,triangulation.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-23311,w=0.1,e=20,suface.png
| |
| − | File:COVID-19-23311,w=0.1,e=20,triangulation.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Min-Edge = 20:''' [https://odu.box.com/s/dkv6271ky0cxvk4lio2bvw6jv9zw5iaf Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| − |
| |
| − | '''Adaptive with Min-Edge = 20:''' [https://odu.box.com/s/jeqmz2c8dsssl8zujkywl2v3bjaby8gc Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| − |
| |
| − | Meshes generated based on the image [https://phil.cdc.gov//PHIL_Images/23311/23311.tif 23311] retrieved from the [https://www.cdc.gov/media/subtopic/images.htm Centers for Disease Control and Prevention]. For the uniform mesh, the edge-size corresponds to 20 pixels. The adaptive was created by controlling the size of the elements based on the difference in the intensity of the pixels.
| |
| − |
| |
| − | ==COVID-19-23354==
| |
| − | * [https://odu.box.com/s/vwse25rtxemv27sf8vkzofupc4l5mnc7 Input Image]
| |
| − | * 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
| |
| − |
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-23354,uniform,e=15,suface.png
| |
| − | File:COVID-19-23354,uniform,e=15,triangulation.png
| |
| − | </gallery>
| |
| − | <gallery mode="packed" heights=250px>
| |
| − | File:COVID-19-23354,w=0.1,e=15,suface.png
| |
| − | File:COVID-19-23354,w=0.1,e=15,triangulation.png
| |
| − | </gallery>
| |
| − |
| |
| − | Commands to generate meshes:
| |
| − |
| |
| − | '''Uniform with Min-Edge = 15:''' [https://odu.box.com/s/g1ujcqm76q0oxa0cm9dderp9tf5hqubt Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| − |
| |
| − | '''Adaptive with Min-Edge = 15:''' [https://odu.box.com/s/bf0w2cfh7ww8wsm45e9yfxahiwb1m864 Output Mesh]
| |
| − | <pre>
| |
| − | 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
| |
| − | </pre>
| |
| − |
| |
| − | Meshes generated based on the image [https://phil.cdc.gov//PHIL_Images/23354/23354.tif 23354] retrieved from the [https://www.cdc.gov/media/subtopic/images.htm Centers for Disease Control and Prevention]. For the uniform mesh, the edge-size corresponds to 15 pixels. The adaptive was created by controlling the size of the elements based on the difference in the intensity of the pixels.
| |
