Contents. User FAQ: Installation & Generic What is Slicer?
3D Slicer is:. A software platform for the analysis (including registration and interactive segmentation) and visualization (including volume rendering) of medical images and for research in image guided therapy. A free, software available on multiple operating systems: Linux, MacOSX and Windows. Extensible, with powerful for adding algorithms and applications. Where can I download Slicer?
3DSlicer is available for download by visiting the following link: Where can I download older release of Slicer? Older releases of 3DSlicer are available here: How to install Slicer?. Go to. Click on the link corresponding to your operating system. Linux MacOSX Windows Start a terminal and type these commands: $ tar xzvf /Downloads/Slicer-4.3.0-linux-amd64.tar.gz -C / $ cd /Slicer-4.3.0-linux-amd64 $./Slicer. Double click on the downloaded Slicer-4.3.0-linux-amd64.exe package.
6.40 I have some DICOM images that I want to reslice at an arbitrary angle; 6.41 I have to manually segment a large number of slices. Double click on the downloaded Slicer-4.3.0-linux-amd64.exe package. Image Size, Total Points, 10,000, 50,000, 100,000, 200,000, 1%, 2%, 5%, 10%, 20%. Total Image Slicer Keygen Mac. 7/15/2017 0 Comments Download Art. At risk of scrutiny here as i’m a total noob with my mates decks but-I’m still only able to play around with the demo- i. VirtualDJ 8 records, edits, and mixes digital audio and video from a wide range of sources for free. V8 is no mere upgrade but a significant.
Follow instructions displayed on the screen. Double click on the downloaded Slicer-4.3.0-linux-amd64.dmg package. Drag & drop the Slicer.app onto your Desktop or in your Applications.
Is slicer really free? Yes, really, truly, free.
Not just a free trial. No pro version with all the good stuff. Slicer is free with no strings attached. You can even re-use the code in any way you want with no royalties and you don't even need to ask us for permission. (Of course we're always happy to hear from people who've found slicer interesting).
See for the legal version of this. Can I use slicer for patient care? Slicer is intended for research work and has no FDA clearances or approvals of any kind. It is the responsibility of the user to comply with all laws and regulations (and moral/ethical guidelines) when using slicer.
How to cite Slicer? Please cite the Slicer web site and the following publications when publishing work that uses or incorporates Slicer.
Slicer 4. Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F., Sonka M., Buatti J., Aylward S.R., Miller J.V., Pieper S., Kikinis R. Magnetic Resonance Imaging 2012; July PMID: 22770690. Slicer 3. Pieper S, Lorensen B, Schroeder W, Kikinis R.
Proceedings of the 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2006; 1:698-701. Pieper S, Halle M, Kikinis R.
Proceedings of the 1st IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2004; 1:632-635. Slicer 2. Gering, David T., Arya Nabavi, Ron Kikinis, Noby Hata, Lauren J. O'Donnell, W. Grimson, Ferenc A. Jolesz, Peter M.
Black, and William M. Journal of Magnetic Resonance Imaging 13, no. 6 (2001): 967-975. Gering D, Nabavi A, Kikinis R, Grimson W, Hata N, Everett P, Jolesz F, Wells W. Int Conf Med Image Comput Comput Assist Interv. How do I create an account for the Slicer wiki?
Please note: You only need an account if you want to edit or add pages. Follow the Log in-Request Account link from the upper right corner of the slicer wiki page. Once the account request is approved, you will be e-mailed a notification message and the account will be usable at log in. What if I have problems with Slicer installation? You can read our guide explaining. How to uninstall Slicer?.
On Windows, choose 'Uninstall' option from the Start menu. On the Mac, remove the Slicer.app file. To clean up settings, remove '/.config/www.na-mic.org/'. On Linux, remove the directory where the application is located. To clean up settings, remove '/.config/NA-MIC/' Where can I find Slicer tutorials?
Slicer tutorials associated with the latest 4.8 stable release are available by visiting the following link:. I read errors in the logs complaining about memory Errors such as “Description: Failed to allocate memory for image.” indicate that you don’t have enough memory space. This can be a common issue if you run a 32-bit version of Slicer. You cannot expect a 32-bit executable to deal with any moderately complex problem. The is to download/build/use Slicer in 64-bit mode.
Possible workarounds:. Use a 64-bit version of Slicer. You have somewhat more memory if you run the module in a separate process.
To do that open and check the “Prefer Executable CLIs” option, then restart Slicer. Decrease the size and/or resolution of the input and output images. Consider to focus on just your area of interest. Consider or increase the sample spacing (decrease the resolution) of your data. Which Slicer version should I use: 3.X or 4.X? In general slicer3 and slicer4 have roughly similar functionality with respect to registration basics. Probably the most important thing to keep in mind is that slicer3 is no longer actively maintained.
Slicer4, on the other hand, has benefited from literally hundreds of bug fixes over the past several years, and typically has better features and much better performance. Also, the nightly builds of slicer4 are now using ITKv4, which has significantly improved registration code. I am told by active users/developers of ITK that ITKv4 should provide significantly better results in many cases. Also, several new registration techniques are being actively developed for slicer4. Source: What is my HOME folder?
Linux or MacOSX Windows Start a terminal. $ echo /home/jchris Start Command Prompt (Start Menu - All Programs - Accessories - Command Prompt) echo%userprofile% C: Users jcfr What to do if Slicer hang while loading data from an unresponsive network directory? On linux, the hotfix is to umount force the network directory. From a terminal, type the following: sudo umount /mount/point -f Make sure to NOT autocomplete the path with TAB.
This will 'unfreeze' Slicer and allow you to save your work in a different directory. The problem was originally reported as Slicer issue and the proposed solution was suggested by on User FAQ: User Interface How to overlay 2 volumes?. the two volumes. Use the to select one of the volumes as the foreground and one as the background. Change the opacity of the Foreground to your liking.
If you click on the link symbol, this happens to all viewers How to load data from a sequence of jpg files?. Choose from the menu: File / Add Data. Click Choose File(s) to Add button and select any of the files in the sequence in the displayed dialog. Click on Show Options and uncheck the Single File option. Click OK to load the volume.
Go to the Volumes module. Choose the loaded image as Active Volume. In the Volume Information section set the correct Image Spacing and Image Origin values Note that most image processing algorithms only work on grayscale images. Use the Vector to scalar volume module to convert your image to grayscale.
User FAQ: Extensions What is an extension? 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. you can find example cases in the, which includes example datasets and step-by-step instructions. Find an example closest to your scenario and Slicer version and perform the registration steps recommended there. How do I initialize/align images with very different orientations and no overlap? I would like to register two datasets, but the centers of the two images are so different that they don't overlap at all. Is there a way to pre-register them automatically or manually to create an initial starting transformation?.
Manual Recenter: See the 1. Select the image to recenter from the Active Volume menu 3. Select/open the Volume Information tab. 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. Repeat steps 2-4 for the other image volumes 6. In the slice view menu, click on the Fit to Window button (a small square next to the pin in the top left corner of each view) 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. Automatic Initialization: Most registration tools have initializers that should take care of the initial alignment in a scenario you described. However since they often are based on heuristics they may work well in some cases and not in others. The two modules that offer the most initializer options are (under Registration menu) and the. initializers:.
Initialization Transform: here you can specify a transform from which to start. You can perform a manual alignment (see here for tutorial) and then feed this as initializer here. Initialization Transform Mode: these options generate automated initializations for you:. 'Off assumes that the physical space of the images are close, and that centering in terms of the image Origins is a good starting point. useCenterOfHeadAlign: recommended for registering brain MRI where all or most of the head is within the FOV.
useMomentsAlign: recommended for image pairs with similar contrast, scale and content. useGeometryAlign: recommended for image pairs with similar FOV for both objects. This aligns the image grid volumes disregarding of content. useCenterOfROIAlign': recommended if you have a mask for each image that defines the regions you want registered.
This will initialize based on those two masks. Tip: yo can run the registration with just the initializer to see what kind of transformation it produces.
In that case select a Slicer Linear Transform output but leave all boxes under Registration Phases unchecked. initializers:. 'None directly starts with optimization from the current position. CentersOfMass: recommended for image pairs with similar contrast, scale and content. Similar to useMomentsAlign above. SecondMoments: same as above, but also calculating (principal) axis directions. Image Centers': similar to useGeometryAlign above: recommended for image pairs with similar FOV for both objects.
This aligns the image grid volumes disregarding of content. Can I manually adjust or correct a registration? Yes for linear (rigid to affine) transforms; not without resampling for nonrigid transforms. 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. Before attempting manual correction, it is usually advisable to retry an automated run with modified parameters, additional initializers or masks. You can adjust/correct an obtained registration manually, within limits.
There's a brief (no sound) video that demonstrates the procedure here: 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.
Or (maybe safer) you can create an additional new transform and nest the old one inside it. Then once you approve of the adjustment merge the two (via Harden Transform). Go to the, right click on the node labeled 'Scene' and select 'Insert Transform' from the pulldown menu. You should see a new transform node being added to the tree, named 'LinearTransform1' or similar. left click on the volume you wish to register, and drag it onto the new transform node.
You should see a '+' appear in front of the transform node, and clicking on it should reveal the volume now inside/under that transform. make sure you have the image for which you wish to adjust the registration selected and visible in the slice views, preferably all 3 views (sagittal, coronal, axial).
Switch to the and (if not selected already) select the newly created transform from the Active Transform menu. 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.
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. The library is organized in several different ways, e.g. Consult this.
Note that registration methods are in continuous development, and not all cases in the, may be updated for the latest version. To see which version they were verified on, check the icon in the title of the case page. What's the purpose of masking / VOI in registration?
/ What does the masking option in registration accomplish? 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. Automated registration based on image intensity is easily dominated by the portions in the image that contain the most contrast/content. If you have much content that is present in only one image, masking that area out will prevent it from leading the registration astray. Masking provides the opportunity to specify the important 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:.: in the Mask Option tab, you can specify a mask for both fixed and moving image. Note that you need to specify both and that both need to be labelmaps with value 1 in areas you wish included and 0 elsewhere.
Also both mask images must be the same size (image dimensions) as the image being registered; i.e. If you register two images of different size you cannot use the same mask for both, because the mask for the fixed image must match the fixed image size and the mask for the moving image must match the moving image size. But you can use the to resample one mask to the resolution of the other (use the appropriate image as Reference) and then you can use it. see in the Advanced Registration Parameters tab:you can specify 1 mask for the fixed image only. Mask should be a labelmap with value 1 in areas you wish included and 0 elsewhere. 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. You will notice that you're free to continue using other Slicer functions while a registration is running.
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. check your input:. did you provide both a fixed and a moving image?. did you select an output (transform and/or new output volume)?. do the two images have any overlap?
Can you see them both in the slice views? If not try to. When rerunning the registration, try selecting an initializer. are inputs consistent? Will complain if you check a 'BSpline' registration phase but do not select a BSpline output transform, or if you request masking and do not specify masking input or output.
if above checks reveal nothing, open the Error Log window (Window Menu) and scroll to the bottom to see the most recent 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. 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. 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 and inform them of the error.
We're keen on learning so we can improve the program. The fastest and best reply you will get if you copy and paste the error messages found in the Error Log into your mail. 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 manual 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. re-run the registration with parameter modifications:.
if images have little initial overlap or are far apart in orientation, try a (different) initializer: e.g. Has several initializers, details in their documentation and also. do the two images have any overlap? Can you see them both in the slice views? If not try to. When. try a lower DOF registration first to see if that fails.
If the lower DOF fails, subsequent ones will also. For nonrigid registration, try adding intermediate steps, such as a similarity (7 DOF) or Affine (12 DOF) transform. if automated initializers do not help, try a. This need not be perfect, as long as it establishes good overlap and roughly same direction. Then try rerunning the registration using the manual transform as a starting point. ( Initialization Transform) in the. if initial overlap is ok but registration 'drifts away', there is either insufficient sample data or distracting image content.
Try increasing the number of sample points. 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. 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. 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 performs this task. you can adjust/correct an obtained registration manually, within limits, as outlined.
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.: 50,000. Rigid 1%; Affine 2%, BSpline 10%.: 100,000 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.
If your object fills only half the image, double the sample points to get the desired amount of points within the object. By masking we mean to selectively include only parts of an image to selectively participate (i.e contribute to the optimization). Masking is supported directly by. the. the )module Note that the use of masks differs among these: 'Expert Auto' requires a binary mask for fixed image only, while 'General BRAINS' requires masks for both fixed and moving image.
Expected is a label map with values 0 and 1, 1 being the regions to include. Is there a function to convert a box ROI into a volume labelmap?
Slicer version 3.6 supports conversion of a box ROI into a labelmap via the. This function has not (yet) been ported to Slicer4.
You can create a new ROI box or select an existing one. You must select an image volume to crop for the operation, even if you're only interested in the ROI labelmap. You need not select a dedicated output for the labelmap, it is generated automatically when the cropped volume is produced, and will be called SubvolumeROILabel in the MRML tree. After creating the box ROI labelmap, simply delete the cropped volume and other output like the '.resample-scale-1.0' volume. Likely you will need the volume with the same dimension and pixel spacing as the reference image. The box volume produced above has the correct dimension, but is only 1 voxel in size. Hence there is a second step required, which is to resample the SubvolumeROILabel to the same resolution: use the and select the appropriate reference and Nearest Neighbor as interpolation method.
Finally go to the Volumes module and check the Labelmap box in the info tab to turn the volume into a labelmap. Physical Space vs. Image Space: how do I align two registered images to the same image grid? Slicer displays all data in a physical coordinate system. Hence an image can only be displayed correctly if it contains sufficient header information to relate the image voxel grid with physical space.
This includes voxel size, axis orientation and scan order. It is therefore possible for two images to be aligned when viewed in Slicer, even though their underlying image grid is oriented very differently. To match the two images in image as well as physical space, the abovementioned axis direction, voxel size and image grid orientation must match. The procedure will depend on the image data, but the main tools at your disposal are the and. Is there a way to perform an Eddy current correction on DWI in Slicer There is a way, you need to download the GTRACT extension (you can get it from the menu View-Extension Manager) Once you have it you will see a new module category under the diffusion one called 'GTRACT'. Within this category there is a module called 'Coregister B-values'. This module takes a DWI image and outputs a DWI image in which every DWI is co-registered to one of the B0 images (by default the first one), this can be regarded as motion correction.
Within this module there is a checkbox in the 'Registration Parameters' section: 'Eddy Current Correction'. This will tune some of the registration parameters such that some Eddy Current artifacts are corrected. The registration transform file saved by Slicer does not seem to match what is shown When executing the following procedure:. Create a transform. The brian jonestown massacre tepid peppermint wonderland rarlab. Adjust it by adjusting the 6 slider bars in the Transforms module. Save the transform as a.tfm file.
Inspect the contents of the.tfm file in a text editor, and compare them to what is shown in the 4x4 matrix in the Transforms module. re-load the.tfm back into slicer and confirm you have the same data as you saved from slicer. You will notice that, even though the reloaded transform does match, the contents of the.tfm file and what is displayed in the Transforms module do not match. The explanation of this is kind of buried in the details of transforms. The issue relates to the difference between slicer which uses a 'computer graphics' view of the world and itk which uses an 'image processing' view of the world. By this we mean that in slicer you have a matrix hierarchy and you think in terms of moving an object from one spot to another - so a transform that has a positive 'superior' value wrapped around a volume moves the volume up in patient space.
But ITK thinks of transformations in terms of mapping backwards from the display space back to the original image. Imagine if you are stepping sequentially through the output pixels then ITK wants to know the transform that takes you back to the input pixels that it needs to use to calculate the output. This modeling vs. Resampling issue is in addition to the LPS/RAS issue, which is the 2nd (invisible) difference between the two transforms. In Summarry:. The transform represented in the widget is in RAS.
The transform represented in the tfm file is in LPS. The transform represented in the file is the inverse of the transform in the widget (plus it has the LPS/RAS conversion applied). The order of the parameters in the tfm are the elements of the upper 3x3 of the transform displayed in the widget followed by the elements in the last column of the widget. As an example:. take the transform from the widget: - c = 0.996918 -0.078459 -0.000000 6.899965; 0.068016 0.864225 -0.498488 -95.999726; 0.039111 0.496951 0.866896 266.299559; 0.0 0.000000 -0.000000 1.000000. Take the inverse - inv(c) = 0.9969 0.0680 0.0391 -10.7644 -0.0785 0.8642 0.4970 -48.8313 -0.0000 -0.4985 0.8669 -278.7091 0 0 0 1.0000 3. LPS to RAS conversion will take you all the way to what is the file, i.e.
Pre and post multiply inv(c) by the respective matrices. How can I see the parameters of the function that describe a BSpline registration/deformation? To see the parameters of the transform, you have to write it to file and investigate by other means. The BSpline transform is saved as a ITK.tfm which is a text file containing the displacement vectors of each grid-point, plus any initial affine transform (if present).
One nice way to visualize is to create a grid image of the same dimensions as your target, and then apply the transform to this grid image, you can then see the deformations as deformations in the gridlines. Use the for the resampling. A quick way directly in slicer is to place the undeformed and deformed volumes into back- and foreground and fade back and forth with the fading slider. Another alternative is to convert the transform into a 4-D deformation field directly and visualize it in slicer using RGB color. How can I convert a BSpline transform into a deformation field? There is commandline functionality in Slicer to convert a BSpline ITK transform file (.tfm) into a deformation field volume. To execute, type (exchange /Applications/Slicer3.6.3 with the path of your Slicer installation): /Applications/Slicer3.6.3/Slicer3 -launch /Applications/Slicer3.6.3/lib/Slicer3/Plugins/BSplineToDeformationField -tfm InputBSpline.tfm -refImage ReferenceImage.nrrd -defImage OutputDeformationField.nrrd for more details try: /Applications/Slicer3.6.3/Slicer3 -launch /Applications/Slicer3.6.3/lib/Slicer3/Plugins/BSplineToDeformationField -help My reoriented image returns to original position when saved; Problem with the Harden Transform function.
You can apply an affine transform to an image by creating a transform, placing the volume inside that transform in the Data module, and then selecting Harden Transform via the context-menu (right click on the image volume). This will move the image back out to the main level and 'apply' the transform. It will, however, not resample the image data, but rather place the information about the new orientation into the image header.
When the image is saved, this information is saved also as part of the file header, as long as orientation data is supported by the file format. If the saved volume is now loaded by another software that does not consider this header orientation (e.g. ImageJ) or does not visualize the image in physical space, then the image will appear in its old position. While resampling of data is best avoided if possible, a hard resampling is possible through the: select your image and transform as input, create a new volume as output and click Apply.
This new volume will now be in the new orientation that will be retained if saved and reloaded elsewhere. What is the Meaning of 'Fixed Parameters' in the transform file (.tfm) of a BSpline registration?
A typical BSpline transform file will contain 2 transforms, an affine portion (commonly saved as 'Transform 1' at the end of the file), and a nonrigid BSpline portion (commonly saved as 'Transform 0'). The bulk of the BSpline part are 3D displacement vectors for each of the BSpline grid-nodes in physical space, i.e. For each grid-node, there will be three blocks of displacements defining dx,dy,dz for all grid nodes.
After this field is a 'Fixed Parameters' section that may look like this: FixedParameters: 8 8 8 -54.1406 -54.1406 - 54.1406 35 1 0 0 0 1 0 0 0 1 The first 3 numbers are the actual grid size (number of knots in each dimension), which is always larger than your requested grid because the grid is extended beyond the image margin to prevent clipping. The next 3 numbers is the origin of the grid, spacing of the grid, and the direction cosines of the grid. More details on the format in the I have some DICOM images that I want to reslice at an arbitrary angle There's several ways to go about this. If you wish to register your image to another reference/target image, run one of the automated registration methods. If you wish to realign manually, most efficient way is to use the.
Once you have the desired orientation, you need to apply the new orientation to the image. You can do this in 2 ways: 1) without or 2) with resampling the image data. Without resampling: In the Data module, select the image (inside the transforms node) and select 'Harden Transforms' from the pulldown menu. This will write the new orientation in physical space into the image header. This will work only if other software you use and the image format you save it as support this form of orientation information in the image header. With resampling: Go to the and create a new image by resampling the original with the new transform.
This will incur interpolation blurring but is guaranteed to transfer for all image formats or software. For more details on manual transform, see and the. I have to manually segment a large number of slices. How can I make the process faster? Contour every other slice, then run a Dilate and an Erode operation. For further speed increase (at the cost of losing more details), you may contour just every 3rd or 4th slice and then run Dilate multiple times (until all the holes are filled in) and then run Erode as many times as you ran Dilate. You can also subsample your image first, then edit, and finally upsample again and use the SmoothLabelmap module to reduce artifacts.
See FAQ below for examples on quick segmentation methods. How can I quickly generate a mask image? Several tools exist to interactively segment structures. A collection of short video examples demonstrating the methods can be found here: After registration the registered image appears cropped. How can I increase the field of view to see/include the entire image Problem: The registration results seems to be correct but the output volume shows only the overlapping region. Is there a way that to show the whole registered volume including the parts which are not overlapping? There's two answers to this problem: one is a visualization issue related to how Slicer chooses the field of view (FOV), and one is how the FOV is chosen for resampling.
Slice views: Slicer sets the overall field of view based on the image selected as 'background'. If the image in the foreground extends beyond that region it will be clipped. You can easily fix/test that by switching foreground and background volumes.
If you already created a resampled version of the registered image, that may also have been cropped,because it sets the field of view based on the reference image (which is the fixed image usually). If you place your resampled image in the background and still see cropped edges, then that's what happened. In that case either use a different reference image for resampling or no reference at all and specify the result sizes manually, or use the crop tool to expand the FOV as described below:.
use the to over-crop the reference image (define ROI to cover the field of view you want to have in the resampled volume). You will need to use interpolated crop mode, so the resolution will not match the original reference volume. Use the result of the cropping operation as the reference for (you will need to specify the moving volume, output volume, and the transform produced by the BRAINS registration module). User FAQ: Models How can I transform a model for output?
Slicer performs all operations in millimeters, and all anatomy is referenced to the patient space. When the data from from DICOM or other formats with well-defined geometry mappings, all the dimensions are handled automatically. However some output formats, such as.stl format, do not have defined physical units, and some software will insist that data be saved with respect to units other than millimeters. In this case, you can pre-transform the data before saving using the following steps:. Create a linear transform using the. Enter the conversion factor along the main diagonal of the transform matrix (i.e. If the export should be in meters rather than millimeters, then enter 0.001 in place of 1.0 along the three locations in the main diagonal).
Apply the new transform to the model (it will appear much smaller now in slicer). Go to the. Right-click on the model. Pick the Harden Transform menu item.
The model will not change size, but it will move out of the transform, meaning that the internal data points have been changed and is ready for saving. User FAQ: Scripting Should I learn Python 2.X or 3.X?
Since Slicer is currently built against python 2.7.3, we suggest you to learn python 2.X. To learn more about the difference:. How to grab full slice image (+-volume, +-model)? A Few General Approaches There are multiple ways to access image data from one or all of the slice views.
. Key Features The graphics file has to be selected via file browsing on the hard drives. After that, this program enables users to select the size of the output by width and height as well as some parameters such as colors and frames.
With the same procedure that of slicing, images can also be merged to create a new one. This collage merging function gives users the ability to select the orientation of the image, the model as well as the output file type.
Total Image Slicer can also act as an encoder for graphics files. Apart from slicing images scanned to PDF formats, this tool supports other various formats. It can, for example, work with JPEG, PNG, TIF and BMP files. Pros. Total Image Slicer is a practical tool for processing image files. The interface is intuitive and allowing both beginners and experts to handle it.
Cons. This can only be used for 30 days.