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[[Projects:ARRASuplements|Back to ARRA main page]]
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Back to [[Projects:ARRASuplements|ARRA main page]], [[Projects:RegistrationDocumentation|Registration main page]]
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----
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<br>
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'''Note: the pages below were constructed during the ARRA project cycle and are no longer actively maintained. <br>
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[http://wiki.slicer.org/slicerWiki/index.php/Documentation/Nightly/Registration/RegistrationLibrary The Registration library is still maintained but has moved here]'''
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<br>
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----
  
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[[Projects:RegistrationDocumentation|Back to Registration main page]]
 
 
= The Slicer Registration Case Library =
 
= The Slicer Registration Case Library =
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Welcome to the 3DSlicer Registration Case Library. This page is under continuous development as we add and refine case examples of image registration within 3DSlicer. The goal is for you to find a case here similar to yours that will address the issues of your particular image registration problem. You will find 3 sets of content with each case: 1) a step-by-step tutorial that will show you how to register images of this type, 2) the example dataset used in the tutorial so you can try for yourself , 3) a custom '''Registration Presets''' file that contains the optimized registration parameters that you can load directly into slicer.
 
  
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Here's how to get started:
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{| style="color:#000000; background-color:#aaaaaa;" cellpadding="10" cellspacing="0" border="0"
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*#browse/search the library below for a case similar to yours. If you cannot find one consider our [[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Call for Datasets''']].
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|Welcome to the 3DSlicer Registration Case Library. This page is under continuous development as we add and refine case examples of image registration within 3DSlicer. The goal is for you to find here a case similar enough to your particular image registration problem to provide you with registration parameters, strategies and tutorials. The library is growing by virtue of '''user contributions'''; if you have an interesting case please consider our ''Call for Datasets'' on the right. Successful registration strategies; algorithm choice and parameters vary greatly for different image contrast and content. Each listed case comprises a test dataset to try yourself,  a guided step-by-step '''tutorial''' that will show you how to register the case with 3DSlicer, the solution transform so you can compare, and a custom ''Registration Parameter Presets'' file with optimized registration parameters that you can load directly into slicer.
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*#download the data, preset file and tutorials
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|
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*#run the tutorial on your machine with your installation of slicer
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|[[Image:SlicerRegistrationLibrary_Ad.png|right|300px|link=Projects:RegistrationDocumentation:UseCaseAdvertisement|Slicer Registration Case Library: Call for Example Datasets]] <br>
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*#load the preset file and try that on your own data
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[[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Consider adding your case to the library''']]
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*#if you do not get a satisfactory match with the presets, have a look at the ''Registration Challenges'' and ''Key Strategies''  section on the download page of your case. You will find recommendations there on how to venture forth
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|}
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*#if still unsuccessful you may have a case of interest to the library. Also consider posting a message to the [http://www.slicer.org/pages/Mailinglist slicer user group].
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*Library organized by structure below. [[Projects:RegistrationDocumentation:RegLibTable|'''Library as sortable table see here.''']]
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*See here for detailed [https://www.slicer.org/wiki/Slicer-3-6-FAQ '''Registration FAQ''']
  
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== Source ==
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== BRAIN ==
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Data is collected from a variety of sources. Because we want to focus on the registration problem and not be distracted by image format or other data management issues, the datasets listed here are copied and reformatted. As the data becomes available a download link is added. 
 
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* [[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Call for Datasets''']]
 
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*Options for the download location is a direct link to a download page from the main  [http://www.slicer.org/pages/UserOrientation 3Dslicer user page] or XNAT Central. The former seems preferable, since the general XNAT GUI appears too complex for a simple 1-case download. We expect most users to download only 1 or 2 files closest to their particular use case, not entire study sets. Such download should be acessible with 1-2 clicks, as with other slicer resources.
 
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*Disk usage: Likely these example sets will grow no larger than 10GB. Estimating 50-80MB per case would allow  60-100 cases within a 5GB space.
 
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*Since we post reformatted and preprocessed data, where possible the link to the original source is provided.
 
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*Links here also from the  [[Data|NA-MIC resource page]].To be updated when moving.
 
  
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==Categories & Formatting==
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{| cellpadding="6" cellspacing="2"
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*Ideally we seek 2 sets for each use case to define a range of settings, i.e. one case that is average and works reasonably well, and one case that is more challenging. Both cases together then define a range. The two cases would be posted together, provided the difficult case can be solved with different settings and does not require a different approach. The latter case would then be better listed in a ''Troubleshooting'' category.
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|align="center" |[[Image:Registration_HLogo_IntraMRI.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraMRI]]
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*The main categories will follow along the hierarchies outlined [[Projects:RegistrationDocumentation#Use_Case_Library|here]].
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|align="center" |[[Image:Registration_HLogo_IntraDTI.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraDTI]]
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*We seek to have all datasets in a single-volume file format, most likely '''.nii''' or '''.nrrd'''. This will greatly facilitate file management and case documentation and will also guarantee full anonymization. The NRRD format is defined [http://teem.sourceforge.net/nrrd/index.html here] and the NIFTI format is defined [http://nifti.nimh.nih.gov/nifti-1 here].
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|align="center" |[[Image:Registration_HLogo_IntrafMRI.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraFMRI]]
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*'''Anonymization''': Anonymized data is imperative. In a first pass posting single volume files only that do not contain subject-specific meta data is the safest. Relying on the provider/user to properly anonymize is likely insufficient. It's easy to overlook single DICOM fields.  Defacing algorithms are avail. thru [[Mbirn:_Defacer_for_structural_MRI|MBIRN]] but will affect the result and require the mask to be avail. to the registration.
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|align="center" |[[Image:Registration_HLogo_IntraPET.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraPETCT]]
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*Once formatting, anonymization and description are complete, listing here will be replaced with a download link. Temporarily listed are links to source databases, where avail.
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|-
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*'''Speed''': include speed measurement with each case. Include note in tutorial that speed concerns are built into the default settings, i.e. if results do not look right on first run, there's many options to fine tune, hence the library concept
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraMRI|'''Same Subject Brain MRI''' ]] collection contains '''structural'''MRI of the same subject, e.g. aligning follow-up to baseline or a T1w and a PDw image.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraDTI|'''Same Subject  DTI''' ]] collection contains cases of registering a DTI dataset with an anatomical reference, such as a high-resolution MRI.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraFMRI|'''Same Subject  fMRI''' ]] collection contains cases of registering a fMRI dataset with an anatomical reference, such as a high-resolution MRI.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraPETCT|'''Same Subject  PET/CT/MRI''' ]] collection contains cases of registering a PET or CT dataset with an MRI or CT.
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|-
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|align="center" |[[Image:Registration_HLogo_InterMRI.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:BrainInterMRI]]
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|align="center" |[[Image:Registration_HLogo_InterPET.png‎| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:BrainInterPETCT]]
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|align="center" |[[Image:Registration_HLogo_Atlas.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:BrainAtlas]]
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|
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|-
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainInterMRI|'''Different Subject Brain MRI''' ]] collection contains cases of co-registering MRI of (many) different subjects into a common space. This often includes non-rigid registration (image warping).
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainInterPETCT|'''Different Subject PET/CT''' ]] collection contains cases of registering PET/SPECT/CT images from different subjects, e.g. aligning a SPECT perfusion atlas with an MRI.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainAtlas|'''Different Subject Brain Atlas''' ]] collection contains cases of registering an atlas to a single subject or building atlases from a collection of subjects.
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|
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|}
  
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==Case Inventory Brain==
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== OTHER ==
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*'''[[Projects:RegistrationDocumentation:UseCaseExample1#|Intra-subject Brain (MS): T2 FLAIR + Labelmap to T1 SPGR]]'''
 
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*Intra-subject T1-T2-DTI-fMRI
 
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*Intra-subject T1-T2-DTI
 
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**DTI baseline to T1 inter-subject with clipped FOV
 
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**[[DTI-non-rigid|DTI affine & non-rigid alignment]]
 
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*Intra-subject PD,T2, T1Gd (MS)
 
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**Scan-rescan  intra-subject. No change.
 
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**[http://ij.itk.org/midas/community/view/21 UNC Midas Database of healthy volunteers]
 
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**[[FMRI-to-hires|fMRI: inter-subject structural scan to MNI atlas target]]
 
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*cases with defacing applied with mask avail.
 
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*cases with defacing w/o mask
 
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*example of half-way registration: 2 sets
 
  
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==Case Inventory Non-Brain==
 
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*PET-CT whole body, 2 timepoints each  -- [[media:2009-08-PETCT.zip|see here]]
 
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*breast Cancer MRI: pre- and post-treatment
 
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* breast Cancer - [[media:bcData.zip|original data]], [[media:4jim.zip|two time points after some registration and processing]]
 
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* prostate image database (intra- and inter-subject registration use cases) http://prostatemrimagedatabase.com/index.html
 
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* knee registration for Simbios project -- http://slicer.spl.harvard.edu/slicerWiki/index.php/Stanford_Simbios_group
 
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* liver tumor ablation: pre-procedural MRI to intra-procedural CT --> Dr. Stuart Silverman's IGT group:  [http://www.na-mic.org/publications/item/view/567 manuscript]
 
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* kidney tumor ablation: pre-procedural MRI to intra-procedural CT --> Dr. Stuart Silverman's IGT group
 
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* liver CT, intra-subject,  contrast enhanced  [http://www.na-mic.org/publications/item/view/1702 manuscript]
 
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* temporal bone (ear) intra-subject CT to MRI of the  [http://www.na-mic.org/publications/item/view/257 collab with Soenke in 2005]
 
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* tibia CT,  [http://www.na-mic.org/publications/item/view/339 Model-based surface registration]
 
  
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==Case Inventory Non-human==
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{| cellpadding="6" cellspacing="2"
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*[http://www.bsl.ece.vt.edu/data/vervet_atlas/vervet.php Vervet Atlas]
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|align="center" |[[Image:Registration_HLogo_Abdominal.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Abdominal]]
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|align="center" |[[Image:Registration_HLogo_Knee.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Musculoskeletal]]
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|align="center" |[[Image:Registration_HLogo_WholeBody.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:WholeBody]]
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|align="center" |[[Image:Registration_HLogo_Animal.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Animal]]
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|-
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:Abdominal|'''Abdominal/Thoracic''' ]] collection contains cases of breast and abdominal MRI/CT/PET, e.g. for therapeutic assessment or interventional guidance.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:Musculoskeletal|'''Musculoskeletal''' ]] collection contains cases of aligning musculoskeletal images, e.g. aligning knee MRI images.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:WholeBody|'''Whole Body PET/CT''' ]] collection contains cases of registering different modalities of whole body imaging.
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:Animal|'''Animal MRI/CT''' ]] collection contains cases of aligning animal datasets.
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|-
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|align="center" |[[Image:Registration_HLogo_Auxiliary.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Auxiliary]]
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|-
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|The [[Projects:RegistrationDocumentation:UseCaseInventory:Auxiliary|'''Auxiliary''']] collection contains  images & data that can be useful for performing, visualizing or validating registration.
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|}
  
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==Self-validation Sets==
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== How to get started ==
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These are datasets with artificial misalignment, i.e. the perfect alignment is known.
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*1. browse/search the library for a case similar to yours. The library is organized by organ (brain vs. non-brain), modality (MR, CT, PET), intra- vs. inter-subject). Each case also has a list of keywords, so you may try a direct search for a case matching yours. Or for all cases in a  [[Projects:RegistrationDocumentation:RegLibTable|'''single sortable table  see here.''']]
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*testing PET-CT-MRI on the Vanderbuild database: [http://www.insight-journal.org/RIRE/ RIRE]
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*2. If you find a good match, continue with 3. below. If you cannot find a good match, consider our  [[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Call for Datasets & Registration Service''']].
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*Dual Echo PD/T2 intra subject different contrast self validation
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*3. from the case description page, follow the links to download the data, preset file and tutorials.
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*Isotropic Brain SPGR T1 with single axis rotation
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*4. run the tutorial on your machine with your installation of slicer (v3.6 or higher recommended)
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*[[Projects:RegistrationDocumentation:ParameterTesting|ISMRM '10: Parameter Sensitivity Analysis]]
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*5. load the preset file and try those settings on your own data
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*5. if you do not get a satisfactory registration results with the presets, have a look at the ''Registration Challenges'' and ''Key Strategies''  section on the download page of your case. You will find recommendations there on how to venture forth. Try the recommended adjustments.
 +
*6. if still unsuccessful you may have a case of interest to the library. [[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Consider adding your case to the library for a free registration''']].  Also consider posting a message to the [http://www.slicer.org/pages/Mailinglist slicer user group].
 +
*7. if successful we'd also love to hear:  [[Projects:RegistrationDocumentation:UseCaseAdvertisement|''' We gladly add your case with full acknowledgment to the library''']].
  
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== First 10 cases (not in sequential order) ==
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== Source & Format ==
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*Brain intra-subject, same contrast T1, change detection follow-up: tumor growth
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Data is collected from a variety of sources. Most we hope to originate from user contributions. Because we want to focus on the registration problem and not be distracted by image format or other data management issues, the datasets listed here are reformatted as NRRD files. Cases under construction may be listed, and when complete a download link is added. 
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*Brain MRI, intra-subject, same contrast PD&T2, change detection follow-up: new MS lesions
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*[[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Call for Datasets''']]
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*Brain MRI, intra-subject, different contrast, co-register all series of the same exam: T1 SPGR, FLAIR, T2
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*[[Projects:RegistrationDocumentation:RegLibList|Full List of Registration Library Cases]]
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*Brain MRI, intra-subject, DTI to reference, apply Xform to 25-direction DTI tensor
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*[[Projects:RegistrationDocumentation:RegLibTable|Sortable Table of Library Cases]]
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*Brain MRI, intra-subject, example with clipped FOV, example of masking required
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*[[Projects:RegistrationDocumentation:RegLibDataList|List of downloadable Registration Library data files]]
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*Brain MRI, inter-subject, co-register T1 SPGR to atlas dataset (ICBM). Resample a label map.
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* All image data is anonymized, i.e. there is no identifying or patient specific information in any of the posted data. We do not keep identifiers, so we cannot retrace.  
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*Liver intra-subject,  pre-procedural MRI to intra-procedural CT
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*[[Projects:RegistrationDocumentation:ParameterPresetsTutorial|How to Load/Save Registration Parameter Presets]]
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*Prostate MRI, intra-subject
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*Links here also from the  [[Data|NA-MIC resource page]].To be updated when moving.
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*Knee inter-subject registration to initialize segmentation
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*For a list/overview of registration options '''by method''' see [https://www.slicer.org/wiki/Slicer3:Registration#Registration_in_3D_Slicer the '''3DSlicer Registration Portal Page''']
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*PET to CT Whole Body single timepoint
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[[Category:Registration]]
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*Breast Cancer: feasible with affine focus?
 

Latest revision as of 17:40, 10 July 2017

Home < Projects:RegistrationDocumentation:UseCaseInventory
Back to ARRA main page, Registration main page


Note: the pages below were constructed during the ARRA project cycle and are no longer actively maintained.
The Registration library is still maintained but has moved here

The Slicer Registration Case Library

Welcome to the 3DSlicer Registration Case Library. This page is under continuous development as we add and refine case examples of image registration within 3DSlicer. The goal is for you to find here a case similar enough to your particular image registration problem to provide you with registration parameters, strategies and tutorials. The library is growing by virtue of user contributions; if you have an interesting case please consider our Call for Datasets on the right. Successful registration strategies; algorithm choice and parameters vary greatly for different image contrast and content. Each listed case comprises a test dataset to try yourself, a guided step-by-step tutorial that will show you how to register the case with 3DSlicer, the solution transform so you can compare, and a custom Registration Parameter Presets file with optimized registration parameters that you can load directly into slicer.
Slicer Registration Case Library: Call for Example Datasets

Consider adding your case to the library

BRAIN

Registration HLogo IntraMRI.png Registration HLogo IntraDTI.png Registration HLogo IntrafMRI.png Registration HLogo IntraPET.png
The Same Subject Brain MRI collection contains structuralMRI of the same subject, e.g. aligning follow-up to baseline or a T1w and a PDw image. The Same Subject DTI collection contains cases of registering a DTI dataset with an anatomical reference, such as a high-resolution MRI. The Same Subject fMRI collection contains cases of registering a fMRI dataset with an anatomical reference, such as a high-resolution MRI. The Same Subject PET/CT/MRI collection contains cases of registering a PET or CT dataset with an MRI or CT.
Registration HLogo InterMRI.png Registration HLogo InterPET.png Registration HLogo Atlas.png
The Different Subject Brain MRI collection contains cases of co-registering MRI of (many) different subjects into a common space. This often includes non-rigid registration (image warping). The Different Subject PET/CT collection contains cases of registering PET/SPECT/CT images from different subjects, e.g. aligning a SPECT perfusion atlas with an MRI. The Different Subject Brain Atlas collection contains cases of registering an atlas to a single subject or building atlases from a collection of subjects.

OTHER

Registration HLogo Abdominal.png Registration HLogo Knee.png Registration HLogo WholeBody.png Registration HLogo Animal.png
The Abdominal/Thoracic collection contains cases of breast and abdominal MRI/CT/PET, e.g. for therapeutic assessment or interventional guidance. The Musculoskeletal collection contains cases of aligning musculoskeletal images, e.g. aligning knee MRI images. The Whole Body PET/CT collection contains cases of registering different modalities of whole body imaging. The Animal MRI/CT collection contains cases of aligning animal datasets.
Registration HLogo Auxiliary.png
The Auxiliary collection contains images & data that can be useful for performing, visualizing or validating registration.

How to get started

  • 1. browse/search the library for a case similar to yours. The library is organized by organ (brain vs. non-brain), modality (MR, CT, PET), intra- vs. inter-subject). Each case also has a list of keywords, so you may try a direct search for a case matching yours. Or for all cases in a single sortable table see here.
  • 2. If you find a good match, continue with 3. below. If you cannot find a good match, consider our Call for Datasets & Registration Service.
  • 3. from the case description page, follow the links to download the data, preset file and tutorials.
  • 4. run the tutorial on your machine with your installation of slicer (v3.6 or higher recommended)
  • 5. load the preset file and try those settings on your own data
  • 5. if you do not get a satisfactory registration results with the presets, have a look at the Registration Challenges and Key Strategies section on the download page of your case. You will find recommendations there on how to venture forth. Try the recommended adjustments.
  • 6. if still unsuccessful you may have a case of interest to the library. Consider adding your case to the library for a free registration. Also consider posting a message to the slicer user group.
  • 7. if successful we'd also love to hear: We gladly add your case with full acknowledgment to the library.

Source & Format

Data is collected from a variety of sources. Most we hope to originate from user contributions. Because we want to focus on the registration problem and not be distracted by image format or other data management issues, the datasets listed here are reformatted as NRRD files. Cases under construction may be listed, and when complete a download link is added.

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