https://www.slicer.org/w/api.php?action=feedcontributions&feedformat=atom&user=MurtaSlicer Wiki - User contributions [en]2026-06-13T19:22:16ZUser contributionsMediaWiki 1.33.0https://www.slicer.org/w/index.php?title=Documentation/Nightly/Extensions/BrainVolumeRefinement&diff=64138Documentation/Nightly/Extensions/BrainVolumeRefinement2022-06-29T23:50:49Z<p>Murta: </p>
<hr />
<div><noinclude>{{documentation/versioncheck}}<br />
</noinclude><br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-header}}<br />
<!-- ---------------------------- --><br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}<br />
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}} }}<br />
{{documentation/{{documentation/version}}/module-introduction-row}}<br />
This work was partially funded by CAPES and CNPq, Brazilian Agencies. Information on CAPES can be obtained on the [http://www.capes.gov.br/ CAPES website] and [http://www.cnpq.br/ CNPq website].<br><br />
'''Authors''': Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Fabrício Henrique Simozo, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Prof. Luiz Otávio Murta Junior, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email><br><br />
{{documentation/{{documentation/version}}/module-introduction-row}}<br />
{{documentation/{{documentation/version}}/module-introduction-logo-gallery<br />
|Image:CSIM-logo.png|CSIM Laboratory <br />
|Image:USP-logo.png|University of Sao Paulo<br />
|Image:CNPq-logo.png|CNPq Brazil<br />
|Image:CAPES-logo.png|CAPES Brazil<br />
}}<br />
{{documentation/{{documentation/version}}/module-introduction-end}}<br />
<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Extension Description}}<br />
{{documentation/{{documentation/version}}/module-description}}<br />
{|<br />
[[Image:BVeR-logo.png|left]]<br />
<br />
The Brain Volume Refinement (BVeR) extension is designed to assist neuroscience studies. The BVeR algorithm is suitable for a broad use of healthy brain structural MRI images, e.g. T1w and T2w, offering broad application in many large data analyses. The main contribution of the proposed method is related to the reduction of manual interference in the brain volume refinement after an automatic skull stripping procedure been performed, helping to reduce human errors and processing time. Even though the BVeR method does not provide a fully brain extraction algorithm, it can be helpful as a ''ad hoc'' image processing step in which increase the quality of well-known brain extraction algorithm in the literature. Any brain extracting frameworks can be refined with this method, e.g. FSL-BET, FreeSurfer, BEasT, 3DSkullStrip, ROBEX, OptiBET and many others.<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|Modules}}<br />
* '''Structural T1w and T2w brain volume correction''': [[Documentation/{{documentation/version}}/Modules/BVeR|BVeR]]<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Use Cases}}<br />
Most frequently used for these scenarios:<br />
* Use Case 1: Cortical thickness surface delineation. <br />
**When dealing with grey-matter overestimate due to badly brain extraction step. <br />
* Use Case 2: Brain atrophy<br />
**Assist in the total brain volume estimate also reducing the non-brain tissues belonging outside the grey-matter tissue frontier.<br />
<br />
<gallery widths="400px" heights="400px" perrow="3"><br />
Image:T1-FS.png|T1 weighted MRI Image with FreeSurfer original brain mask overlay (only the out surface is represented)<br />
Image:T1-FS-BVeR.png|Same T1 weighted MRI Image but with BVeR correction mask overlay (using the previous FreeSurfer input)<br />
</gallery><br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|Similar Extensions}}<br />
* NA<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|References}}<br />
* da Silva Senra Filho, A.C., Simozo, F.H. & Murta Junior, L.O. Brain volume refinement (BVeR): automatic correction tool as an alternative to manual intervention on brain segmentation. Res. Biomed. Eng. 37, 631–640 (2021). https://doi.org/10.1007/s42600-021-00168-x<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|Information for Developers}}<br />
{{documentation/{{documentation/version}}/extension-developerinfo}}<br />
<br />
Repositories:<br />
<br />
*Source code: [https://github.com/CSIM-Toolkits/SlicerBrainVolumeRefinement GitHub repository]<br />
*Issue tracker: [https://github.com/CSIM-Toolkits/SlicerBrainVolumeRefinement/issues open issues and enhancement requests]<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-footer}}<br />
<!-- ---------------------------- --></div>Murtahttps://www.slicer.org/w/index.php?title=Documentation/Nightly/Extensions/BrainVolumeRefinement&diff=64137Documentation/Nightly/Extensions/BrainVolumeRefinement2022-06-29T23:49:27Z<p>Murta: </p>
<hr />
<div><noinclude>{{documentation/versioncheck}}<br />
</noinclude><br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-header}}<br />
<!-- ---------------------------- --><br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}<br />
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}} }}<br />
{{documentation/{{documentation/version}}/module-introduction-row}}<br />
This work was partially funded by CAPES and CNPq, Brazilian Agencies. Information on CAPES can be obtained on the [http://www.capes.gov.br/ CAPES website] and [http://www.cnpq.br/ CNPq website].<br><br />
'''Authors''': Antonio Carlos da S. Senra Filho, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Fabrício Henrique Simozo, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Prof. Luiz Otávio Murta Junior, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Contact: Antonio Carlos da S. Senra Filho <email>acsenrafilho@usp.br</email><br><br />
{{documentation/{{documentation/version}}/module-introduction-row}}<br />
{{documentation/{{documentation/version}}/module-introduction-logo-gallery<br />
|Image:CSIM-logo.png|CSIM Laboratory <br />
|Image:USP-logo.png|University of Sao Paulo<br />
|Image:CNPq-logo.png|CNPq Brazil<br />
|Image:CAPES-logo.png|CAPES Brazil<br />
}}<br />
{{documentation/{{documentation/version}}/module-introduction-end}}<br />
<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Extension Description}}<br />
{{documentation/{{documentation/version}}/module-description}}<br />
{|<br />
[[Image:BVeR-logo.png|left]]<br />
<br />
The Brain Volume Refinement (BVeR) extension is designed to assist neuroscience studies. The BVeR algorithm is suitable for a broad use of healthy brain structural MRI images, e.g. T1w and T2w, offering broad application in many large data analyses. The main contribution of the proposed method is related to the reduction of manual interference in the brain volume refinement after an automatic skull stripping procedure been performed, helping to reduce human errors and processing time. Even though the BVeR method does not provide a fully brain extraction algorithm, it can be helpful as a ''ad hoc'' image processing step in which increase the quality of well-known brain extraction algorithm in the literature. Any brain extracting frameworks can be refined with this method, e.g. FSL-BET, FreeSurfer, BEasT, 3DSkullStrip, ROBEX, OptiBET and many others.<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|Modules}}<br />
* '''Structural T1w and T2w brain volume correction''': [[Documentation/{{documentation/version}}/Modules/BVeR|BVeR]]<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Use Cases}}<br />
Most frequently used for these scenarios:<br />
* Use Case 1: Cortical thickness surface delineation. <br />
**When dealing with grey-matter overestimate due to badly brain extraction step. <br />
* Use Case 2: Brain atrophy<br />
**Assist in the total brain volume estimate also reducing the non-brain tissues belonging outside the grey-matter tissue frontier.<br />
<br />
<gallery widths="400px" heights="400px" perrow="3"><br />
Image:T1-FS.png|T1 weighted MRI Image with FreeSurfer original brain mask overlay (only the out surface is represented)<br />
Image:T1-FS-BVeR.png|Same T1 weighted MRI Image but with BVeR correction mask overlay (using the previous FreeSurfer input)<br />
</gallery><br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|Similar Extensions}}<br />
* NA<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|References}}<br />
* da Silva Senra Filho, A.C., Simozo, F.H. & Junior, L.O.M. Brain volume refinement (BVeR): automatic correction tool as an alternative to manual intervention on brain segmentation. Res. Biomed. Eng. 37, 631–640 (2021). https://doi.org/10.1007/s42600-021-00168-x<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-section|Information for Developers}}<br />
{{documentation/{{documentation/version}}/extension-developerinfo}}<br />
<br />
Repositories:<br />
<br />
*Source code: [https://github.com/CSIM-Toolkits/SlicerBrainVolumeRefinement GitHub repository]<br />
*Issue tracker: [https://github.com/CSIM-Toolkits/SlicerBrainVolumeRefinement/issues open issues and enhancement requests]<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/extension-footer}}<br />
<!-- ---------------------------- --></div>Murtahttps://www.slicer.org/w/index.php?title=Documentation/Nightly/Modules/MSLesionSimulator&diff=60815Documentation/Nightly/Modules/MSLesionSimulator2019-02-25T17:09:03Z<p>Murta: </p>
<hr />
<div><noinclude>{{documentation/versioncheck}}</noinclude><br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-header}}<br />
<!-- ---------------------------- --><br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Introduction and Acknowledgements}}<br />
{{documentation/{{documentation/version}}/module-introduction-start|{{documentation/modulename}}}}<br />
{{documentation/{{documentation/version}}/module-introduction-row}}<br />
Extension: [[Documentation/{{documentation/version}}/Extensions/LesionSimulator|Lesion Simulator]]<br><br />
Webpage: http://dcm.ffclrp.usp.br/csim/<br><br />
Author: Antonio Carlos da S. Senra Filho and Fabrício Henrique Simozo, CSIM Laboratory (University of Sao Paulo, Department of Computing and Mathematics)<br><br />
Contact: Antonio Carlos da S. Senra Filho, <email>acsenrafilho@usp.br</email> - Fabrício Henrique Simozo, <email>fsimozo@gmail.com</email><br><br />
{{documentation/{{documentation/version}}/module-introduction-row}}<br />
{{documentation/{{documentation/version}}/module-introduction-logo-gallery<br />
|Image:CSIM-logo.png|CSIM Laboratory <br />
|Image:USP-logo.png|University of Sao Paulo<br />
|Image:CAPES-logo.png|CAPES Brazil<br />
}}<br />
{{documentation/{{documentation/version}}/module-introduction-end}}<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Module Description}}<br />
[[File:Mslesionsimulator icon.png|right]]<br />
<br />
This module offer <br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Use Cases}}<br />
* Use Case 1: Simulate different anatomical/clinical MS lesions patterns on healthy individuals MRI images<br />
**In the baseline scan approach, it is offered a simulation procedure where a determined lesion load is reconstructed using a subject specific anatomical features, resulting in a realistic MS lesion load simulation.<br />
* Use Case 2: Simulate longitudinal MS lesion progression on clinical healthy individuals MRI images<br />
**Another important issue in Multiple Sclerosis diagnosis is the lesion progression, where drive the therapeutic strategy by the health professionals. In this case, an automatic segmentation approach could be optimally adjusted for the time progression presented in a exam series.<br />
<br />
<gallery widths="200px" heights="200px" perrow="4"><br />
Image:MNI152_orig.png|T1 weighted MRI brain in axial orientation (provided by the ICBM-MNI152 non linear brain template)<br />
Image:MNI152_lesionload40mL.png|The same MNI152 template with 40mL lesion load simulated lesions (axial orientation)<br />
Image:MNI152_orig_sag.png|T1 weighted MRI brain in sagittal orientation (provided by the ICBM-MNI152 non linear brain template)<br />
Image:MNI152_lesionload40mL_sag.png|The same MNI152 template with 40mL lesion load simulated lesions (sagittal orientation)<br />
</gallery><br />
<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Panels and their use}}<br />
<br />
[[Image:mslesionsimulator_gui.png|thumb|500px|User Interface]]<br />
'''Input Parameters:'''<br />
*T1 Volume<br />
**A T1 weighted MRI image from a healthy individual.<br />
*T2 Volume<br />
**A T2 weighted MRI image from a healthy individual.<br />
*T2-FLAIR Volume<br />
**A T2-FLAIR weighted MRI image from a healthy individual.<br />
*PD Volume<br />
**A PD weighted MRI image from a healthy individual.<br />
*DTI-FA Map<br />
**A DTI-FA map from a healthy individual.<br />
*DTI-ADC Map<br />
**A DTI-ADC map from a healthy individual.<br />
*Output Lesion Label<br />
**Pick the output lesion label.<br />
*Return output data in the original space<br />
**Choose if you want to transform the final images to its original space. If not, all the input images will be in T1 space. NOTE: This choice only takes effect on the baseline MS lesion simulation, i.e. the longitudinal lesion simulation (if checked) will always return the data using the T1 space.<br />
*Is brain extraced?<br />
**Is the input data already brain extracted? This information is only used for MNI152 template, where it helps to the registration process.<br />
<br />
'''MS Lesion Simulation Parameters:'''<br />
*Lesion Load<br />
**Set the desired lesion load to be used for MS lesion generation.<br />
*Sigma<br />
**Choose the Gaussian variance to be applied in the final lesion map. The scale is given in mm.<br />
*Lesion Homogeneity<br />
**Choose the lesion homogeneity present in the lesion simulation. Lower values give a more heterogenous lesion contrast. This parameter is related to a Gaussian variance given in mm.<br />
*Lesion Variability<br />
**Choose the lesion independent variability level that represents how distinct is each non-connected lesion regarding the voxel intensity gray level. This measure simulates the independent progression for each lesion, where a higher value indicates higher variability among lesions. The parameter is modulated by the normal standard deviation depending of the image type inserted<br />
<br />
'''MS Longitudinal Lesion Simulation Parameters:'''<br />
*Simulate Longitudinal Exams?<br />
**Simulate an additional longitudinal sequence (given the same input data)? If checked, the MS Lesion Simulator tool will recreate a sequence of exams with longitudinal MS lesion pattern.<br />
*Follow-ups<br />
**Set the desired number of follow-up acquisitions that will be simulated.<br />
*Changing Contrast Balance<br />
**Set the percentage of lesions that will change its original signal state along the follow-ups.<br />
*Output Follow-Up<br />
**Output folder where follow-up image files will be saved.<br />
<br />
'''Advanced Parameters:'''<br />
*White Matter Threshold<br />
**Set the White Matter threshold used to refine the simulated lesion map. The simulation supose that the MS lesions belongs only in the White Matter space. This variable is related to the voxel intensity and the White Matter probability distribution (standard deviation).<br />
*Percentage Of Samples<br />
**Percentage of voxel used in registration.<br />
*BSpline Grid<br />
**Set the BSpline grid for non linear structural adjustments.<br />
*Initiation Method<br />
**Initialization method used for the MNI152 registration.<br />
<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Similar Modules}}<br />
N/A<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|References}}<br />
SENRA FILHO, ANTONIO CARLOS DA SILVA; SIMOZO, FABRÍCIO HENRIQUE; DOS SANTOS, ANTÔNIO CARLOS; MURTA JR, LUIZ OTAVIO<br />
Multiple Sclerosis multimodal lesion simulation tool (MS-MIST). BIOMEDICAL PHYSICS & ENGINEERING EXPRESS. , 2019. http://dx.doi.org/10.1088/2057-1976/ab08fc<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-section|Information for Developers}}<br />
{{documentation/{{documentation/version}}/module-developerinfo}}<br />
<br />
<!-- ---------------------------- --><br />
{{documentation/{{documentation/version}}/module-footer}}<br />
<!-- ---------------------------- --></div>Murta