View source for Slicer-3-6-FAQ

 [[Documentation-3.6#Introduction|Back to Slicer 3.6 Introduction]]

This page contains frequently asked questions related to Slicer 3.6
= '''User FAQ: Installation & Generic''' =
== Is slicer3 ready for end users yet? ==
Yes!  See [http://slicer.org the home page].
== DLL Problems on Windows ==
''I just download the 3D Slicer binaries for Windows and unpacked it. When I doubleclicked the file "slice2-win32-x86.ext", it gave out the error message''
''can't find package vtk while executing "package require vtk" invoked from within "set::SLICER(VTK_VERSION) [package require vtk]" (file "C:/slicer2/Base/tck/Go.tck" line 483). ''
We've seen this sort of thing happen when you have incompatible dll's installed.  E.g. so programs will install a vtkCommon.dll into your window system folder and windows tries to use it instead of the one that comes with windows.  You could try doing a search for vtk*.dll in your system and remove or rename any that are not in slicer as a test.

= '''User FAQ: Segmentation''' =
== Interactive Editor: I would like to segment more than one structure==
Use the [[Modules:Editor-Documentation-3.6|Per-Structure Volumes feature]] to create label volumes for each structure that you would like to segment interactively. After successful segmentation of all the structures, the individual label volumes can be merged.

= '''User FAQ: Diffusion''' =

==I have DICOM DWI images. What do I need to do to process them in Slicer?==
DWI formats are not properly standardized (as of 2010). In many cases, vendors put important information about gradients into the private fields. Our [[Modules:DicomToNRRD-3.6|DICOM to NRRD converter]] has an extensive library of such special cases. Convert your DWI images to a NRRD volume, before beginning the post processing.==
==I want to register my diffusion scan to a structural scan==
[[Slicer-3-6-FAQ#How_do_I_register_a_DWI_image_dataset_to_a_structural_reference_scan.3F_.28Cookbook.29|See DWI registration FAQ here]]

==I have streamlines from DTI and would like to find the subset which goes through a particular region==
The [[Modules:ROISelect-Documentation-3.6|ROI selection module]] in Slicer 3.6 allows to filter for streamlines which pass (or do not pass) through label map ROI's

= User FAQ : installation & general use = 


= '''User FAQ : Registration''' = 

== How do I fix a wrong image orientation? / My image appears upside down / facing the wrong way / I have incorrect/missing axis orientation ==
*'''Problem:''' My image appears upside down / flipped / facing the wrong way / I have incorrect/missing axis orientation
*'''Explanation:''' Slicer presents and interacts with images in ''physical'' space, which differs from the way the image is stored by a separate ''transform'' that defines how large the voxels are and how the image is oriented in space, e.g. which side is left or right.  This information is stored in the image header, and different image file formats have different ways of storing this information. If Slicer supports the image format, it should read the information in the header and display the image correctly. If the image appears upside down or with distorted aspect ratio etc, then the image header information is either missing or incorrect. 
*'''Fix:''' You can correct the voxel dimensions and the image origin in the Info tab of the [http://www.slicer.org/slicerWiki/index.php/Modules:Volumes-Documentation-3.6 Volumes module], and you can reorient images via the [http://www.slicer.org/slicerWiki/index.php/Modules:Transforms-Documentation-3.6 Transforms module]. Reorientation however will work only if the incorrect orientation involves rotation or translation. If axes are flipped (e.g. if left & right are flipped because the x-axis direction is defined incorrectly), then there is no tool in Slicer to alter that. This is by design; Slicer does not want to offer tools to (inadvertedly) manipulate image information that should be static and could lead to misrepresented image data. 
*However fixing incorrect orientations such as flipped axes is not that hard and can be done with the help of Slicer:
:1. load the image into slicer (Load Volume, Add Data,Load Scene..)
:2. save the image back out as ''NRRD (.nhdr)'' format.
:3. open the ''.nhdr'' with a text editor of your choice. You should see a line that looks like this:
  space: left-posterior-superior
  sizes: 448 448 128
  space directions: (0.5,0,0) (0,0.5,0) (0,0,0.8)
:4. the three brackets ( ) represent the coordinate axes as defined in the ''space'' line above, i.e. the first one is left-right, the second anterior-posterior, and the last inferior-superior. To flip an axis place a minus sign in front of the respective number, which is the voxel dimension. E.g. to flip left-right, change the line to
  space directions: ('''-'''0.5,0,0) (0,0.5,0) (0,0,0.8)
:5. alternatively if the entire orientation is wrong, i.e. coronal slices appear in the axial view etc., you may easier just change the ''space'' field to the proper orientation. Note that Slicer uses ''RAS'' space by default, i.e. first (x) axis = left-'''r'''ight, second (y) axis = posterior-'''a'''nterior, third (z) axis = inferior-'''s'''uperior
:6. save & close the edited ''.nhdr'' file and reload the image in slicer to see if the orientation is now correct.

== What do the coordinate labels R,A,S and (negative numbers) mean? ==

== How do I fix incorrect voxel size / aspect ratio of a loaded image volume? ==
*'''Problem:''' My image appears distorted / stretched / with incorrect aspect ratio
*'''Explanation:''' Slicer presents and interacts with images in ''physical'' space, which differs from the way the image is stored by a set of separate information that represents the physical "voxel size" and the direction/spatial orientation of the axes. If the voxel dimensions are incorrect or missing, the image will be displayed in a distorted fashion.  This information is stored in the image header. If the information is missing, a default of isotropic 1 x 1 x 1 mm size is assumed for the voxel.
*'''Fix:''' You can correct the voxel dimensions and the image origin in the Info tab of the [http://www.slicer.org/slicerWiki/index.php/Modules:Volumes-Documentation-3.6 Volumes module]. If you know the correct voxel size, enter it in the fields provided and hit RETURN after each entry. You should see the display update immediately. Ideally you should try to maintain the original image header information from the point of acquisition. Sometimes this information is lost in format conversion. Try an alternative converter or image format if you know that the voxel size is correctly stored in the original image. Alternatively you can try to edit the information in the image header, e.g. save the volume as (NRRD (.nhdr) format and open the ".nhdr" file with a text editor.

== How do I register images that are very far apart / do not overlap ==
*'''Problem:''' when you place one image in the background and another in the foreground, the one in the foreground will not be visible (entirely) when switching bak & forth
*'''Explanation:'''Slicer chooses the field of view (FOV) for the display based on the image selected for the background. The FOV will therefore be centered around what is defined in that image's origin. If two images have origins that differ significantly, they cannot be viewed well simultaneously.
*'''Fix:''' recenter one or both images as follows:
:1. Go to the [http://www.slicer.org/slicerWiki/index.php/Modules:Volumes-Documentation-3.6 Volumes module], 
:2. Select the image to recenter from the ''Actrive Volume'' menu
:3. Select the ''Info'' tab.
:4. Click the ''Center Volume'' button. You will notice how the image origin numbers displayed above the button change. If you have the image selected as foreground or background, you may see it move to a new location.
:5. Repeat steps 2-4 for the other image volumes
:6. From the slice view menu, select ''Fit to Window''
:7. Images should now be roughly in the same space. Note that this re-centering is considered a change to the image volume, and Slicer will mark the image for saving next time you select ''Save''.

== How do I register a DWI image dataset to a structural reference scan? (Cookbook) ==
*'''Problem:''' The DWI/DTI image is not in the same orientation as the reference image that I would like to use to locate particular anatomy; the DWI image is distorted and does not line up well with the structural images
*'''Explanation:''' DWI images are often acquired as EPI sequences that contain significant distortions, particularly in the frontal areas. Also because the image is acquired before or after the structural scans, the subject may have moved in between and the position is no longer the same. 
*'''Fix:''' obtain a baseline image from the DWI sequence, register that with the structural image and then apply the obtained transform to the DTI tensor. The two chief issues with this procedure deal with the difference in image contrast between the DWI and the structural scan, and with the common anisotropy of DWI data.
* Overall Strategy and detailed instructions for registration & resampling can be found in our [[http://na-mic.org/Wiki/index.php/Projects:SlicerFAQ:DWI_Registration '''DWI registration cookbook''']]
* you can find example cases in the [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraDTI '''DWI chapter of the Slicer Registration Case Library'''], which includes example datasets and step-by-step instructions. Find an example closest to your scenario and perform the registration steps recommended there.

== Can I manually adjust or correct a registration? ==
*'''Problem:''' obtained registration is insufficient
*'''Explanation:''' The automated registration algorithms (except for  fiducial and surface registration) in Slicer operate on image intensity and try to move images so that similar image content is aligned. This is influenced by many factors such as image contrast, resolution, voxel anisotropy, artifacts such as motion or intensity inhomogeneity, pathology etc, the initial misalignment and the parameters selected for the registration.
*'''Fix:''' you can adjust/correct an obtained registration manually, within limits. As outlined below. Your first try however should be to obtain a better automated registration by changing some of the input and/parameters and then re-run. Some guidelines on this are listed [[Slicer3:FAQ#Registration result is wrong or worse than before?|'''in this FAQ''']]
**'''Manual Adjustment''': If the transform is linear, i.e. a rigid or affine transform, you can access the rigid components (translation and rotation) of that transform via the [http://www.slicer.org/slicerWiki/index.php/Modules:Transforms-Documentation-3.6 Transforms module]. 
***#In the ''Data'' module, drag the image volume inside the registration transform node
***#Select the views so that the volume is displayed in the slice views
***#Go to the [http://www.slicer.org/slicerWiki/index.php/Modules:Transforms-Documentation-3.6 Transforms module] and adjust the translation and rotation sliders to adjust the current position. To get a finer degree of control, enter smaller numbers for the translation limits and enter rotation angles numerically in increments of a few degrees at a time

== What's the difference between the various registration methods listed in Slicer? ==
Most of the registration modules use the same underlying ITK registration algorithm for cost function and optimization, but differ in implementation on parameter selection, initialization and the type of image toward which they have been tailored. To help choose the best one for you '''based on the method or available options''', an [http://www.slicer.org/slicerWiki/index.php/Slicer3:Registration#Registration_in_3D_Slicer overview of all registration methods] incl. [http://www.slicer.org/slicerWiki/index.php/Registration:Categories a '''comparison matrix''' can be found here]. <br>
To help choose '''based on a particular image type and content''', you will find many example cases incl. step-by-step instructions and discussions on the particular registration challenges in the [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:UseCaseInventory '''Slicer Registration Library''']. The library is organized in several different ways, e.g. consult this [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable '''sortable table''' with all cases and the method used].<br>
There is also a brief overview within Slicer that helps distinguish: Select the ''Registration Welcome'' option at the top of the Modules/Registration menu.

== What's the purpose of masking / VOI in registration? ==
*'''Problem:''' What does the masking option in some of the registration modules accomplish ?
*'''Explanation:''' The masking option is a very effective tool to focus the registration onto the image content that is most important. It is often the case that the  alignment of the two images is more important in some areas than others. ''Masking'' provides the opportunity to specify those regions and make the algorithm ignore the image content outside the mask. This does not mean that the rest is not registered, but rather that it moves along passively, i.e. areas outside the mask do not actively contribute to the cost function that determines the quality of the match. Note the mask defines the areas to ''include'', i.e. to exclude a particular region, build a mask that contains the entire object/image except that region.
*'''Note:''' masking within the registration is different from feeding a masked/stripped image as input, where areas of no interest have been erased. Such masking can still produce valuable results and is a viable option if the module in question does not provide a direct masking option. But direct masking by erasing portions of the image content can produce sharp edges that registration methods can lock onto. If the edge becomes dominant then the resulting registration will be only as good as the accuracy of the masking. That problem does not occur when using masking option within the module.
*The following modules currently (v.3.6.1) provide masking:
**[http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit '''BRAINSFit''']
***found under: ''Masking Options'' tab
***requires mask for both fixed and moving image
***has option to automatically generate masks
***some initialization modes (''CenterOfHeadAlign'') will not work in conjunction with masks
**[http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 '''Expert Automated Registration''']
***found under: ''Advanced Registration Parameters'' tab
***requires mask for fixed image only
**[http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImagesMultiRes-Documentation-3.6 '''Robust Multiresolution Affine''']
***found under: ''Optional'' tab
***requires mask for fixed image only
***provides option to define a mask as a box ROI
**[http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSDemonWarp '''BRAINSDemonWarp''']
***found under: ''Mask Options'' tab
***requires mask for both fixed and moving image
***has option to automatically generate masks

== Registration failed with an error. What should I try next? ==
*'''Problem:''' automated registration fails, status message says "completed with error" or similar.
*'''Explanation:''' Registration methods are mostly implemented as commandline modules, where the input to the algorithm is provided as temporary files and the algorithm then seeks a solution independently from the activity of the Slicer GUI. Several reasons can lead to failure, most commonly they are wrong or inconsistent input or lack of convergence if images are too far apart initially.
*'''Fix''': open the ''Error Log'' window (Window Menu) and click on the most recent (top) entries related to the registration. Usually you will see a ''commandline'' entry that shows which arguments were given to the algorithm, and a ''standard output'' or similar that lists what the algorithm returned. More detailed error info can be found in either this entry, or in the ''ERROR: ..." line at the top of the list. Click on the corresponding line and look for explanation in the provided text. If there was a problem with the input arguments or the that would be reported here.
**for example, running Robust Multiresolution Affine without input will report: "No input data assigned"  etc.
*If the Error log does not provide useful clues, try varying some of the parameters. Note that if the algorithm aborts/fails right away and returns immediately with an error, most likely some input is wrong/inconsistent or missing.
*if variation does not succeed, try an alternative registration module. Some are more tailored toward particular image modalities and DOF than others
*check the initial misalignment, if images are too far apart and there is no overlap, registration may fail. Consider initialization with a prior manual alignment, centering the images or using one of the initialization methods provided by the modules
*write to the  [mailto:slicer-users@bwh.harvard.edu '''Slicer user group''' (slicer-users@bwh.harvard.edu)] and inform them of the error. We're keen on learning so we can improve the program. Helpful to copy and paste the error messages found in the Error Log.

== Registration result is wrong or worse than before? ==
*'''Problem:''' automated registration provides an alignment that is insufficient, possibly worse than the initial position
*'''Explanation:''' The automated registration algorithms (except for  fiducial and surface registration) in Slicer operate on image intensity and try to move images so that similar image content is aligned. This is influenced by many factors such as image contrast, resolution, voxel anisotropy, artifacts such as motion or intensity inhomogeneity, pathology etc, the initial misalignment and the parameters selected for the registration.
*'''Fix:'''  Your first try however should be to obtain a better automated registration by changing some of to re-run the automated registration, while changing either initial position, initialization method, parameters or the method/module used. Most helpful to determine a good secondary approach is to know why the first one was likely to fail. Below a list of possible reasons and the remedies:
**'''too much initial misalignment:''' particularly rotation can be difficult for automated registration to capture. If the two images have strong rotational misalignment, consider A) one of the initialization options (e.g. [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] or [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated]), B) a manual initial alignment using the [http://www.slicer.org/slicerWiki/index.php/Modules:Transforms-Documentation-3.6 Transforms module] and then use this as initialization input
**'''insufficient detail:''' consider increasing the number of sample points used for the registration, depending on time/speed constraints, increase to 5-10% of image size. 
**'''insufficient contrast:''' consider adjusting the ''Histogram Bins'' (where avail.) to tune the algorithm to weigh small intensity variations more or less heavily
**'''strong anisotropy:''' if one or both of the images have strong voxel anisotropy of ratios 5 or more, rotational alignment may become increasingly difficult for an automated method. Consider increasing the sample points and reducing the ''Histogram Bins''.  In extreme cases you may need to switch to a manual or fiducial-based approach
**'''distracting image content:''' pathology, strong edges, clipped FOV with image content at the border of the image can easily dominate the cost function driving the registration algorithm. '''Masking''' is a powerful remedy for this problem: create a mask (binary labelmap/segmentation) that excludes the distracting parts and includes only those areas of the image where matching content exists. This requires one of the modules that supports masking input, such as: [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSFit], [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 ExpertAutomated], [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImagesMultiRes-Documentation-3.6 Multi Resolution]. Next best thing to use with modules that do not support masking is to mask the image manually and create a temporary masked image where the excluded content is set to 0 intensity; the ''Mask Volume'' module performs this task
**'''too many/too few DOF''': the degrees of freedom (DOF) determine how much motion is allowed for the image to be registered. Too few DOF results in suboptimal alignment; too many DOF can result in overfitting or the algorithm getting stuck in local extrema, or a bad fit with some local detail matched but the rest misaligned.  Consider a stepwise approach where the DOF are gradually increased. [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] and [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated] provide such pipelines; or you can nest the transforms manually. A multi-resolution approach can also greatly benefit difficult registration challenges: this scheme runs multiple registrations at increasing amounts of image detail. The [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImagesMultiRes-Documentation-3.6 Robust Multiresolution module] performs this task.
**'''inappropriate algorithm:''' there are many different registration methods available in Slicer. Have a look at the [http://www.slicer.org/slicerWiki/index.php/Slicer3:Registration '''Registration Method Overview'''] and consider one of the alternatives. Also review the [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable '''sortable table''' in the Registration Case Library] to see which methods were successfully used on cases matching your own.
**you can adjust/correct an obtained registration manually, within limits, as outlined [[Slicer3:FAQ#Can I manually adjust or correct a registration?|'''in this FAQ''']].

== How many sample points should I choose for my registration? ==
*'''Problem:''' unsure what the ''Sample Points'' setting means or how I could use it to improve my registration.
*'''Explanation:'''All registration modules contain a parameter field that controls how much of the image is sampled when performing an automated registration. The unit is often an absolute count, but in some cases also a percentage. Default settings also vary among modules. The number of samples is an important setting that determines both registration speed and quality. If the sample number is too small, registration may fail because it is driven by image content that insufficiently represents the image. If sample number is too large, registration can slow down significantly.
*'''Fix:''' If registration speed is not a major issue, better to err on the side of larger samples. Most default settings are chosen to yield relatively fast registrations and for most of today's image represent only a small percentage.  Below the defaults for the different registration modules, for version 3.6.1:
  '''Defaults Used in Slicer Modules v.3.6.1'''
  Fast Rigid / Linear: 10,000
  Fast Affine: 10,000
  Fast Rigid: 10,000
  Fast Non-Rigid BSpline: 50,000
  Expert Automated (Rigid): 1%
  Expert Automated (Affine): 2%
  Expert Automated (BSpline): 10%
  BRAINSfit: 100,000
  BRAINSdemon Warp: N/A 
  Robust Multiresolution: N/A
  Surface Registration: 200
 
The table below relates total sample points and percentages to the most common image sizes. Also consider that sample points are chosen randomly so that some points may fall outside the actual object to be registered. That is not a bad thing per se, some background points are important, but not if they are too far from the edges of the object. So consider both total image size as well as the percentage of the image field of view that your object of interest obtains. E.g. if your object fills only half the image, double the sample points to get the desired amount of points within the object.

{| class="wikitable sortable labelpage labelpagetable" border="1"
|-
! Image Size
! Total Points	
! 10,000
! 50,000
! 100,000
! 200,000
! 1%
! 2%	
! 5%	
! 10%	
! 20%
|-
| 128 x 128 x 64
|1048576
|1.0%
|4.8%
|9.5%
|19.1%
|~10000
|~20000
|~52500
|~100000
|~200000
|-
|-
| 256 x 256 x 30
|1966080
|0.5%
|2.5%
|5.1%
|10.2%
|~20000
|~40000
|~97500
|~200000
|~400000
|-
|-
| 256 x 256 x 120
|7864320
|0.1%
|0.6%
|1.3%
|2.5%
|~77500
|~150000
|~400000
|~775000
|~1500000
|-
|-
| 192 x 192 x 192
|7077888
|0.1%
|0.7%
|1.4%
|2.8%
|~70000
|~150000
|~350000
|~700000
|~1500000
|-
|-
| 512 x 512 x 48
|12582912
|0.1%
|0.4%
|0.8%
|1.6%
|~125000
|~250000
|~625000
|~1250000
|~2500000
|-
|-
| 256 x 256 x 256
|16777216
|0.1%
|0.3%
|0.6%
|1.2%
|~175000
|~325000
|~850000
|~1750000
|~3250000
|-
|-
| 512 x 512 x 160
|41943040
|0.0%
|0.1%
|0.2%
|0.5%
|~425000
|~850000
|~2000000
|~4250000
|~8500000
|}

== I want to register two images with different intensity/contrast. ==
*The two most critical image features that determine automated registration accuracy and robustness are image contrast and resolution. Differences in image contrast are best addressed with the appropriate cost function. The cost function that has proven most reliable for registering images with different contrast (e.g. a T1 MRI to a T2 or an MRI to CT or PET) is '''mutual information'''. All intensity-based registration modules use mutual information as the default cost function. Only the [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 ''Expert Automated Registration''] module lets you choose alternative cost function.

No extra adjustment is therefore needed in terms of adjusting parameters to register images of different contrast. Depending on  the amount of differences you may consider masking to exclude distracting image content or adjusting the ''Histogram Bins'' setting to increase/decrease the level of intensity detail the algorithm is aware of.

== How important is bias field correction / intensity inhomogeneity correction? ==
While registration may still succeed with mild cases of inhomogeneity, moderate to severe inhomogeneity can negatively affect automated registration quality. It is recommended to run an automated bias-field correction on both images before registration. [http://www.slicer.org/slicerWiki/index.php/Modules:N4ITKBiasFieldCorrection-Documentation-3.6 see here for documentation on this module]. Masking of non-essential peripheral structures can also help to reduce distracting image content. [http://www.slicer.org/slicerWiki/index.php/Slicer-3-6-FAQ#What.27s_the_purpose_of_masking_.2F_VOI_in_registration.3F See here for more on masking]

== Have the Slicer registration methods been validated? ==
The Slicer3.6 registration modules share the same same underlying ITK registration engines. For validation of those basic algorithms refer to the ITK software guide or the Insight Journal.  Slicer registration of images and surfaces has been applied successfully in many cases, some of which are documented here [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:UseCaseInventory here]. For ongoing efforts on improving/validating Slicer registration performance please contact the [mailto:slicer-users@bwh.harvard.edu Slicer User Mailing List]   or the  [mailto:slicer-devel@bwh.harvard.edu Slicer Developer Mailing List].

== I want to register many image pairs of the same type. Can I use Slicer registration in batch mode? ==

== How can I save the parameter settings I have selected for later use or sharing? ==
The ''Parameter Set'' menu at the top tab of each module serves this purpose of saving and recalling instances of parameter settings. To save the current settings select ''Rename'' from the menu, give it a descriptive name and then select ''Create New Commandline Module'' from the menu. New settings are added to the menu as created. These settings are saved together with the Slicer Scene.mrml file. To save only tthe presets without any associate data, first save your entire scene, then delete all nodes in the MRML tree except the top ''Scene'' node, and then save this under a new name like "Slicer_Presets.mrml" etc.  To load the presets in, use ''Import'' from the File menu, which will add the MRML entries to the existing scene.  Do not load presets via "Load Scene", since that will delete all currently loaded data. [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:ParameterPresetsTutorial A detailed user guide on loading presets can be found here]

== Registration is too slow. How can I speed up my registration? ==
The key parameters that influence registration speed are the number of sample points, the degrees of freedom of the transform, the type of similarity metric and the initial misalignment and image contrast/content differences. If registration quality is ok, try reducing the sample points first. [http://www.slicer.org/slicerWiki/index.php/Slicer-3-6-FAQ#How_many_sample_points_should_I_choose_for_my_registration.3F Guidelines on selecting sample points are given here]. The degrees of freedom usually are given by the overall task and not subject to variation, but depending on initial misalignment, both speed and robustness can improve by an iterative approach that gradually increases DOF rather than starting with a high DOF setting. The [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit module] and [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated Registration module] both allow prescriptions of iterative DOF.<br>
If using a cost/criterion function other than mutual information, note that the corresponding ITK implementation may not have been parallelized and hence may not be taking advantage of multi-threading/multi-CPU cores on your computer. This can slow down performance significantly. <br>
[http://www.slicer.org/slicerWiki/index.php/Slicer3:Registration Also see the ''Slicer Registration Portal Page'' for help on selecting registration methods based on criteria of speed, precision etc.]

== Registration results are inconsistent and don't work on some image pairs. Are there ways to make registration more robust? ==
The key parameters that influence registration robustness are the number of sample points, the initial degrees of freedom of the transform, the type of similarity metric and the initial misalignment and image contrast/content differences.  particularly initialization methods that seek a first alignment before beginning the optimization can make things worse. If initial position is already sufficiently close (i.e. more than 70% overlap and less than 20% rotational misalignment), consider turning off initialization if available (e.g. in [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] or [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated]). 
Try increasing the sample points. [http://www.slicer.org/slicerWiki/index.php/Slicer-3-6-FAQ#How_many_sample_points_should_I_choose_for_my_registration.3F Guidelines on selecting sample points are given here]. The degrees of freedom usually are given by the overall task and not subject to variation, but depending on initial misalignment,  robustness can greatly improve by an iterative approach that gradually increases DOF rather than starting with a high DOF setting. The [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit module] and [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated Registration module] both allow prescriptions of iterative DOF. Also the [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImagesMultiRes-Documentation-3.6 Multiresolution] module steps through multiple cycles of different image coarseness which is aimed primarily at robustness<br>
If using a cost/criterion function other than mutual information, note that MI tends to be the most forgiving/robust toward differences in image contrast. <br>
[http://www.slicer.org/slicerWiki/index.php/Slicer3:Registration Also see the ''Slicer Registration Portal Page'' for help on selecting registration methods based on criteria of robustness, speed, precision etc.]

== One of my images has a clipped field of view. Can I still use automated registration? ==
Probably yes. Best remedy is to apply a mask that also clips the missing portion in the other image, or better still 2 masks that include the full region of interest that is to be registered and is present in both images. Also initialization is critical, more so than with full FOV images. If images have large amount of initial misalignment, try to center both first (''Volumes/Info/Center Image'') or perform a cursory manual alignment and use that as initialization. Examples of registrations with clipped FOV can be found [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLib_04_MultipleSclerosis here in the Registration Case Library].

== I ran a registration but cannot see the result. How do I visualize the result transform? ==
There are 2 ways to see the result of a registration: 1) by creating a new resampled volume that represents the moving image in the new orientation , 2) by direct (dynamic) rendering of the original image in a new space when placed inside a transform.  The latter is '''not''' available for non-rigid transforms, hence a registration that includes nonlinear components (BSpline, Warp) must be visualized by first resampling the entire volume with the new transform. If you ran a registration yet see no effect, the reason could be one of the following:
*you did not request an output. In the module parameters section, you must specify either an output transform or an output image/volume. Select one or both (for nonrigid registration).
*you requested a result transform but the moving volume is not placed inside the transform in the MRML tree. Not all modules automatically place the moving image inside the result transform node: The [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated Module], for example, does not , so in that case do this manually in the ''Data'' module by dragging the moving volume node inside the result transform.
*registration completed with an error. Check for status messages at the top of the module and look at the ''Error Log''  in the window menu to see if there were any errors reported.
*you performed a non-rigid (BSpline) transform but did not yet request an output volume. To do so after registration is complete, use the [http://www.slicer.org/slicerWiki/index.php/Modules:ResampleScalarVectorDWIVolume-Documentation-3.6 Resample DWI/Vector module].

== What's the difference between Rigid and Affine registration? ==
Rigid registration is a transform with 6 degrees of freedom (DOF): 3 translations (one along each axis) and 3 rotations (one around each axis). An affine registration includes 12 DOF, i.e. 3 additional DOF for scaling (along each axis) and shearing. So strictly speaking an affine transform is a non-rigid transform, even though linear, because the volume can distort. However in practice by ''non-rigid'' transform one usually refers to nonlinear transforms with more than 12 DOF, e.g. BSpline or polynomial models.

== What's the difference between Affine and BSpline registration? ==
An affine registration includes 12 DOF, i.e. 3 for translations (one along each axis),  3 rotations (one around each axis), 3  for scaling (along each axis) and 3 for shearing. So strictly speaking an affine transform is a non-rigid transform, even though linear, because the volume can distort. However in practice by non-rigid transform one usually refers to nonlinear transforms with more than 12 DOF, e.g. BSpline or polynomial models. A BSpline registration employs a nonlinear nonrigid model that allows individual regions of the image to distort independently, but enforcing smooth transitions between them.  A BSpline transform is not described by a 4x4 matrix like the affine model, but by a list of displacement vectors for each point along a prescribed grid. E.g. a 3x3x3 BSpline grid has 27 points that can move independently, yielding 27 DOF; a 5x5x5 grid analogously has 125 DOF etc.

== The nonrigid (BSpline) registration transform does not seem to be nonrigid or does not show up correctly. ==
See FAQ on viewing registration results [http://www.slicer.org/slicerWiki/index.php/Slicer-3-6-FAQ#I_ran_a_registration_but_cannot_see_the_result._How_do_I_visualize_the_result_transform.3F here].
BSpline transforms are '''not''' available for immediate rendering by placing volumes or models inside the transforms. Only linear transforms can be viewed that way. A BSpline transform must be visualized by resampling the entire volume with the new transform. If you did not yet an output volume when running the registration, you can do so after the fact, use the [http://www.slicer.org/slicerWiki/index.php/Modules:ResampleScalarVectorDWIVolume-Documentation-3.6 Resample DWI/Vector module].

== Can I combine multiple registrations? ==

== Can I combine image and surface registration? ==

== What's the difference between BRAINSfit and BRAINSDemonWarp? ==

== Is the BRAINSfit registration for brain images only? ==

== What's the difference between Fast Rigid and Linear Registration? ==

== Which registration methods offer non-rigid transforms? ==

== Which registration methods offer masking? ==


= '''Developer FAQ''' =

== Where can I find out about writing code for slicer3? ==

The [[Slicer3:Developers|Developers]] page has lots of information.