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[[EMSegmenter-Overview|Return to EMSegmenter Overview Page]] <BR>
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[[File:EMSegmenterLogo.png|center]]
 
=Call for Datasets for the EM Segmenter Use Case Library=
 
=Call for Datasets for the EM Segmenter Use Case Library=
  
Let us help you turn your segmentation problem into a success story. If you have an interesting or vexing segmentation problem that is not yet covered in the Library , send us your case: we will try to segment it for you and design a tailored segmentation approach you can use. We then add the anonymized data to the library and build a guided step-by-step tutorial for it. This is a time and resource limited service available until July 1, 2011. <br>
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Let us help you turn your segmentation problem into a success story. If you have an interesting segmentation problem that is not yet covered in the [[EMSegmenter-Tasks| library ]], send us your case: we will try to segment it for you and design a tailored segmentation approach you can use. We then add the anonymized data to the library and build a guided step-by-step tutorial for it. This is a time and resource limited service available until July 1, 2011. <br>
 
If interested drop a line to '''Dominique.Belhachemi at uphs.upenn.edu''' or '''Kilian.Pohl at uphs.upenn.edu'''
 
If interested drop a line to '''Dominique.Belhachemi at uphs.upenn.edu''' or '''Kilian.Pohl at uphs.upenn.edu'''
 
 
  
 
=What You Will Need To Do=
 
=What You Will Need To Do=
  
 
* just send us an Email with a brief description of the problem
 
* just send us an Email with a brief description of the problem
* send us your image data with the corresponding manual segmentation. Please provide more than 10 instances, so that we can generate a robust atlas.
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* send us your image data with the corresponding (manual) segmentation. Please provide more than 10 instances, so that we can generate a robust atlas. Please also insure that the data can be publicly distributed
 
* save your image data as NRRD or NIFTI files
 
* save your image data as NRRD or NIFTI files
 
* if you are unsuccessful in saving the data as described above (which is the anonymization), see our  [http://wiki.na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:Anonymization Anonymization Instructions] , or let us know and we'll walk you through it.
 
* if you are unsuccessful in saving the data as described above (which is the anonymization), see our  [http://wiki.na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:Anonymization Anonymization Instructions] , or let us know and we'll walk you through it.
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=What We Will Do=
 
=What We Will Do=
  
* based on your manual segmentations we will create a atlas
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* based on your segmentations we will create an atlas
 
* we will create a 3DSlicer scene with optimized EM Segmenter parameters for your use case
 
* we will create a 3DSlicer scene with optimized EM Segmenter parameters for your use case
 
* we will send you the final result as well as the procedure and parameters
 
* we will send you the final result as well as the procedure and parameters
* we will add your use case to our library which will become part of a future 3DSlicer version
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* we will add your use case (3DSlicer scene + atlas data) to our [[EMSegmenter-Tasks|Segmentation Task Library]] which will become part of a future 3DSlicer version
 
* this will contain parameters for a successful segmentation which you can load directly into slicer and apply on your data
 
* this will contain parameters for a successful segmentation which you can load directly into slicer and apply on your data
* we will post the anonymized image data as a new case in our Slicer Registration Case Library.
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* this page will also contain a description of your segmentation problem, the exact workflow of obtaining the segmentation, an acknowledgment of your lab and links to your institution and related research paper  
* this page will contain a description of your segmentation problem, the exact workflow of obtaining the segmentation, an acknowledgment of your lab and links to your institution and related research paper  
 
 
* if you can provide us with criteria that define a good segmentation, we will use them in optimization efforts.
 
* if you can provide us with criteria that define a good segmentation, we will use them in optimization efforts.
* example of what the final shared product will look like
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* [[ EMSegmenter-Tasks:MRI-Human-Brain-Parcellation | example of what the final shared product will look like ]]
 
 
  
 
=Limitations/Disclaimer=
 
=Limitations/Disclaimer=
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* this is a time-limited service, available in a first trial until 'July 1, 2011.
 
* this is a time-limited service, available in a first trial until 'July 1, 2011.
 
* depending on workload, we try to get you something within a few weeks, but we cannot guarantee a particular result or a specific turnaround time.
 
* depending on workload, we try to get you something within a few weeks, but we cannot guarantee a particular result or a specific turnaround time.
* all shared data-sets are anonymized:
+
* all shared data-sets are anonymized. Sharing anonymized data in most cases is IRB exempt based on Code of Federal Regulations 45 CFR 46.101(b), which lists as exemption category 4:
      o Sharing anonymized data in most cases is IRB exempt based on Code of Federal Regulations 45 CFR 46.101(b), which lists as exemption category 4:
 
 
 
            Unless otherwise required by department or agency heads, [...] the following categories are exempt [...]:
 
 
 
            4.Research involving the collection or study of existing data, documents, records , pathological specimens,
 
              or diagnostic specimens, if these sources are publicly available or if the information is recorded by the
 
              investigator in  such a manner that subjects cannot be identified, directly or through identifiers linked
 
              to the subjects.
 
  
      o anonymization is easy: load your data into slicer. Save it as NRRD file (in the Save dialog box, make sure 'nrrd' is selected as filetype for all output images). This will save only the raw image data + voxelsize and image orientation. No other data re. subject, scanner or institution are present in the NRRD file. For details see our Anonymization Instructions
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    Unless otherwise required by department or agency heads, [...] the following categories are exempt [...]:
      o if you are unsucessful in anonymizing the data as described above, let us know and we'll walk you through it.
+
   
      o for some high-resolution structural head MRI we may have apply additional "defacing" (i.e. masking of image parts of the face and/or ears) before posting. This removal applies only to image content of facial features that might be recognizable as a 3D rendering. We will do this for you. Only the defaced data is kept.
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    4.Research involving the collection or study of existing data, documents, records , pathological specimens,
 +
    or diagnostic specimens, if these sources are publicly available or if the information is recorded by the  
 +
    investigator in such a manner that subjects cannot be identified, directly or through identifiers linked
 +
    to the subjects.

Latest revision as of 02:25, 27 November 2019

Home < EMSegmenter-UseCaseAdvertisement

Return to EMSegmenter Overview Page

EMSegmenterLogo.png

Call for Datasets for the EM Segmenter Use Case Library

Let us help you turn your segmentation problem into a success story. If you have an interesting segmentation problem that is not yet covered in the library , send us your case: we will try to segment it for you and design a tailored segmentation approach you can use. We then add the anonymized data to the library and build a guided step-by-step tutorial for it. This is a time and resource limited service available until July 1, 2011.
If interested drop a line to Dominique.Belhachemi at uphs.upenn.edu or Kilian.Pohl at uphs.upenn.edu

What You Will Need To Do

  • just send us an Email with a brief description of the problem
  • send us your image data with the corresponding (manual) segmentation. Please provide more than 10 instances, so that we can generate a robust atlas. Please also insure that the data can be publicly distributed
  • save your image data as NRRD or NIFTI files
  • if you are unsuccessful in saving the data as described above (which is the anonymization), see our Anonymization Instructions , or let us know and we'll walk you through it.

What We Will Do

  • based on your segmentations we will create an atlas
  • we will create a 3DSlicer scene with optimized EM Segmenter parameters for your use case
  • we will send you the final result as well as the procedure and parameters
  • we will add your use case (3DSlicer scene + atlas data) to our Segmentation Task Library which will become part of a future 3DSlicer version
  • this will contain parameters for a successful segmentation which you can load directly into slicer and apply on your data
  • this page will also contain a description of your segmentation problem, the exact workflow of obtaining the segmentation, an acknowledgment of your lab and links to your institution and related research paper
  • if you can provide us with criteria that define a good segmentation, we will use them in optimization efforts.
  • example of what the final shared product will look like

Limitations/Disclaimer

  • we can assist only with 3DSlicer software.
  • this is a time-limited service, available in a first trial until 'July 1, 2011.
  • depending on workload, we try to get you something within a few weeks, but we cannot guarantee a particular result or a specific turnaround time.
  • all shared data-sets are anonymized. Sharing anonymized data in most cases is IRB exempt based on Code of Federal Regulations 45 CFR 46.101(b), which lists as exemption category 4:
   Unless otherwise required by department or agency heads, [...] the following categories are exempt [...]: 
   
   4.Research involving the collection or study of existing data, documents, records , pathological specimens, 
   or diagnostic specimens, if these sources are publicly available or if the information is recorded by the 
   investigator in  such a manner that subjects cannot be identified, directly or through identifiers linked 
   to the subjects.