Bioinformatics Example Meshes - Revision history

Spyridon97 at 22:30, 23 July 2020

2020-07-23T22:30:08Z

Spyridon97: /* 2D Example Meshes */

2020-06-02T17:52:53Z

‎2D Example Meshes

Spyridon97: /* 3D Example Meshes */

2020-06-02T16:00:24Z

‎3D Example Meshes

Spyridon97 at 15:57, 2 June 2020

2020-06-02T15:57:11Z

Spyridon97: Created page with "TOC =3D Example Meshes= The directory containing the 3D input data is located in the 3D folder of [https://odu.box.com/s/olefferrnksu2nmerbfvbvsz2u4abbdw Bioninformatics_..."

2020-06-02T15:56:21Z

Created page with "__TOC__ =3D Example Meshes= The directory containing the 3D input data is located in the 3D folder of [https://odu.box.com/s/olefferrnksu2nmerbfvbvsz2u4abbdw Bioninformatics_..."

New page

__TOC__

=3D Example Meshes=
The directory containing the 3D input data is located in the 3D folder of [https://odu.box.com/s/olefferrnksu2nmerbfvbvsz2u4abbdw Bioninformatics_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 COVID-19 Main Protease. 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 COVID-19 NSP15 Endoribonuclease. 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 COVID-19 spike glycoprotein. 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 COVID-19 spike glycoprotein. 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>

=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.

← Older revision		Revision as of 22:30, 23 July 2020
Line 104:		Line 104:

	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].		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].
−
−	~~=2D Example Meshes=~~
−	~~The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/9scj74ix4eulpvgc93sbwte1uvlde8b6 Bioninformatics_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.

← Older revision		Revision as of 15:57, 2 June 2020
Line 104:		Line 104:

	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].		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>~~

	=2D Example Meshes=		=2D Example Meshes=

@@ Line 106: / Line 106: @@
 =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].
+The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/9scj74ix4eulpvgc93sbwte1uvlde8b6 Bioninformatics_Data].
 ==COVID-19-23311==