Difference between revisions of "Slicer:Slicer2.6 Release Notes"
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== Acknowledgements ==
== Acknowledgements ==
This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics. This work was also supported by NIH grant P41 RR13218
This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics. This work was also supported by NIH grant P41 RR13218 http://spl.harvard.edu and the http://www.nbirn.net .
Revision as of 16:38, 21 May 2008Home < Slicer:Slicer2.6 Release Notes
- 1 New Features in Slicer 2.6
- 1.1 Updates to existing modules:
- 1.2 EMSegmenter and EMAtlasBrainClassifier
- 1.3 Additional functionality:
- 1.4 NEW: Comparison Module
- 1.5 System Improvements:
- 2 Building
- 3 Installing
- 4 Known Issues: Base Operations
- 5 Known Issues: Modules
- 6 Reporting Bugs
- 7 Where to go for Help
- 8 Acknowledgements
New Features in Slicer 2.6
Slicer 2.6 has many new features! In addition to numerous bug fixes and other improvements, the list here highlights most major some new features in Slicer 2.6. Please also note that many of these new features are still being developed and will be improved in future releases, so you may encounter some unexpected behaviour. Please send questions about unexpected behavior to the Slicer User's mailing list and reports to the bug tracker.
Updates to existing modules:
- Supports a common fMRI data analysis workflow;
- Currently is appropriate for preprocessed data (which has been slice-timing corrected and motion corrected);
- Allows the specification of blocked, event-related and mixed designs, and the optional concatenation of runs;
- Allows the saving and loading of paradigms;
- Has a more elaborate set of linear modeling tools, including adding temporal derivatives to capture latency in the response, and trend modeling to remove slowly varying nuissance signals;
- Provides an option to pre-whiten the data to account for temporal correlation structure;
- Displays a 'surfable' visualization of the design matrix and contrasts;
- Permits saving and loading of estimated regression weights for use in GLM-based detection;
- Optionally performs grand mean and global mean scaling on input datasets;
- Allows regions of interest (ROIs) to be defined from brain activation 'blobs';
- Provides tools for selecting one or several ROIs and querying statistics on those regions (pop-up histogram plot, with list of max, min, mean p-value, percent signal change, etc.);
- Label maps can be saved and/or used to create 3D models for visualization with multimodality data;
- Reports uncorrected or corrected p-values (using the False Discovery Rate method);
- Allows voxel timecourses to be plotted in regular long or peristimulus histogram form, along with reference signals from the paradigm;
- Provides pop-up help throughout the interface, to provide information on many topics;
- Has a more modular architecture for adding new kinds of brain activation detectors.
New features include:
- Integrated reading of compresed .mgh files (.mgz)
- Improved scalar overlay display, and clickable models for details of scalar values
- .w surface file reading
- Run-time parsing of colour description text files
- FreeSurfer Group Descriptor file reading and plotting of results
- Imrovements to the quality assurance functionality to load a series of subjects and scan through the selected volumes, using the FreeSurfer subject directory structure
New functionality in support of the FMRIEngine work described above.
Many new features including:
- Reading dwi and tensors from nrrd files
- Automatic brain mask generated with tensor estimate
- New scale factor control on scalar generation
- Brighter tracts for all scan orientations
- Tract clustering
- Tensor-to-tensor registation (beta feature, not fully supported)
- Tracts can be rasterized into a label map
EMSegmenter and EMAtlasBrainClassifier
Bug fixes and improvements including new algorithms described here.
- New registration techniques based on ITK registration framework.
- Translation MI: Perorms image registration using 3 translational components based on minimiztion of Mutual Information metric using Regular Step Gradient Descent optimizer.
- Translation Mattes MI: Perorms image registration using 3 translational components based on minimiztion of Mattes Mutual Information metric using Regular Step Gradient Descent optimizer.
- Rigid Mattes MI: Perorms image registration using 3 translational and 3 rotational components based on minimiztion of Mattes Mutual Information metric using Regular Step Gradient Descent optimizer.
- Affine Mattes MI: Perorms image registration using 3 translational, 3 rotational, and 3 scale components based on minimiztion of Mattes Mutual Information metric using Regular Step Gradient Descent optimizer.
- Deformable Demons: Uses Demons algorithm to compute deformation vectors
- Deformable BSpline: Uses BSpline interpolation to compute deformation vectors based on minimiztion of Mattes Mutual Information metric.
- Use TransformVolume module to apply deformation field and linear transformation to resample volumes.
Generic Reader module
- Preserves image orientation and scan order.
- Reads all single component scalar formats supported by ITK I/O factory as of ITK 2.4
Nrrd Reader module
- Support for DTI images (DWI and Tensors).
Image export is re-implemented using ITK image IO mechanism. The following image file formats are supported:
- Analyze (.hdr)
- NRRD(.nrrd) and (.nhrd)
- Meta (.mhd) and (.mha)
- Nifti (.nii), (.img), and (.img.gz)
- VTK (.vtk)
NEW Draw2 Editor
Slicer 2.6 has two manual image editors: Draw (as in Slicer 2.5) and Draw2, which has many new features including:
- High-resolution image editing
- Toggle on/off a cardinal (Catmull-Rom) spline interpolating any control polygon
- Choose sampling density of spline for any polygon
- Select/Move modes automatically toggle based on proximity to selected points, to mimick standard drawing programs; deselect all points by clicking away from the selected points
- Insert mode to allow inserting control points in the middle of a polygon for manual refinement
- Cut, copy, and paste features for control polygons
- Shortcut keys for cut, copy, paste, select all, delete selected, delete all
- Unapply feature: repeatedly click Unapply button to scroll through the applied polygons on any slice at any time and re-edit them
- Can choose whether or not to clear labelmap before each apply operation
- Watch the Simbios Slicer documentation page and Chand's Slicer page for additional information
NEW: Comparison Module
Jermie Anquez of ENST in France contributed a significant set of new functionality for viewing multiple volumes in a coordinated fashion:
- display tab : allows to display up to 9 slices simultaneously (set the
Number of slices using the radio buttons). Use the controls in the top right corner of each slice to set the background, foreground and labelmap displayed. You can fade from background to foreground using the opacity slider. By default, the slices display is independant (linking 'Off' button selected). Each slice has its own orientation, zoom/pan and offset (like in 3D Slicer general framework).
- ** Clicking on Linking 'On' button activates linked display. Specific link
controls are enabled. The orientation, zoom/pan, offset and cursor are then the same on every slice.
- ** The R button resets zoom and pan on every slice (pressing 'r' key over a
slice realizes the same operation)
- mosaik tab : Display a mosaik mixing 2 volumes (useful to check
- ** Set the reference and the second volumes to be displayed.
- Set the number of subdivision, following width and height
- Set the opacity between the reference and the second volume
- Set offset, offset increment and orientation of the mosaik.
- flip tab : Flip the volume following the 3 main axes. This operation doesn't
generate any transform node, but modifies the Volume node.
You don't have to build Slicer yourself to use it. If you want a precompiled version, go here.
To build slicer from source, see Slicer:Slicer_2.6_Building
- distributed versions are built with Microsoft Visual Studio .NET in release mode (note that there may be some problems compiling with .NET 2003)
- We are building using gcc version 3.0.3.
- We are building using gcc version 2.96 on RedHat 7, gcc version 3.2.2 on RedHat 9, and gcc 3.2.3 on RedHat Enterprise Linux.
- Mac OSX
- We are building using gcc version 3.3.
No special installation is needed -- simply unpack the distribution archive and run the platform-specific executable at the top level (for example, slicer2-win32.exe for the Windows build). The slicer distribution contains all the needed support libraries and has been tested on a variety of system configurations.
Known Issues: Base Operations
- All platforms
- If you are having problems running Slicer over an ssh connection with X forwarding, the problem may be that you don't have the appropriate OpenGL libraries on the machine you're sshing from.
Known Issues: Modules
As a research platform, Slicer includes several modules that are not yet fully implemented, but which the developers still felt were far enough along in functionality to provide utility for the community. As such, you may find that some operations do not behave as expected, particularly where they interact with other slicer functions. Please let us know about these issues by filing appropriate bug reports.
Please report bugs for Slicer version 2.5.x. here.
Where to go for Help
This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics. This work was also supported by NIH grant P41 RR13218 NAC and the Biomedical Informatics Research Network.