Difference between revisions of "Wiki help testing"
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**[[Changing Image Contrast|Improving contrast by generating and modifying histograms]] | **[[Changing Image Contrast|Improving contrast by generating and modifying histograms]] | ||
**[[Changing Image Contrast|Using Lookup Table dialog box]] | **[[Changing Image Contrast|Using Lookup Table dialog box]] | ||
| − | **[[Changing Image Contrast#PredefinedLuts|Applying color to images using predefined LUTs ]] | + | **[[Changing Image Contrast#PredefinedLuts|Applying color to images using predefined LUTs]] |
**[[Changing Image Contrast|Comparing images using alphablending]] | **[[Changing Image Contrast|Comparing images using alphablending]] | ||
**[[Changing Image Contrast|Restoring images to their original appearance]] | **[[Changing Image Contrast|Restoring images to their original appearance]] | ||
Revision as of 17:45, 18 April 2012
Contents
Preface
MIPAV Help Volume 1: MIPAV Basics
- Introducing MIPAV
- Installing MIPAV
- Getting Started Quickly with MIPAV
- Allocating Memory in MIPAV
- Opening and loading image files
- MIPAV toolbars
- Displaying MIPAV Toolbars
- Displaying images
- Delineating volumes of interest (VOIs)
- Calculating VOI statistics
- Reviewing the statistics
- Generating graphs (intensity profiles)
- Saving and printing images
- Working with ImageJ
- Customizing MIPAV
- To show the splash screen
- Choosing the default file types to display or save
- Quitting MIPAV
- Graphical and file formats supported by MIPAV
- Understanding Image Basics
- Working with DICOM Images
- Visualizing Images
- Displaying images using the default view
- Displaying images using the animate view
- Displaying images using the cine (movie) view
- Displaying images using the lightbox view
- Displaying images using the link to another image view
- Displaying images using the triplanar view
- Displaying images using the triplanar-dual view
- Displaying images using the surface plotter view
- Displaying images using the surface renderer view
- Displaying images using the volume shear view
- Displaying images using the volume renderer view
- Segmenting Images Using Contours and Masks
- Analyzing Images
- Changing Image Datasets Using MIPAV Utilities
- Standard tasks provided through commands on the Utilities menu
- Recording utilities usage with the history feature
- 4 D tools
- Adding image margins
- Copying images using the Clone command
- Converting image datasets to different data types
- Correcting image spacing
- Cropping images
- Masking (filling) images
- Flipping images
- Image Calculator
- Image Math
- Inverting the image
- Matching images
- Maximum Intensity Projection
- Adding noise to images
- Pad
- Quantify Mask
- Replacing pixel/voxel value in images
- Rotating images
- Slice tools
- Inserting slices into image datasets
- Subtract VOI Background
- Standard tasks provided through commands on the Utilities menu
- Using Scripts (Macros) in MIPAV
- Developing Plugin Programs
- Technical Support
MIPAV Help Volume 2: Algorithms
- DTI Color Display
- Edge Detection: Zero X Laplacian
- Edge Detection: Zero X Non-Maximum Suppression
- Extract Brain: Extract Brain Surface (BET)
- Extract Brain: Extract Brain Surface (BSE)
- Face Anonymizer (BET)
- Fast Fourier Transformation (FFT)
- Filters (Spatial): Adaptive Noise Reduction
- Filters (Frequency)
- Filters (Spatial): Adaptive Path Smooth
- Filters (Spatial) Anisotropic Diffusion
- Filters (Spatial): Coherence-Enhancing Diffusion
- Filters (Spatial): Gaussian Blur
- Filters (Spatial): Gradient Magnitude
- Filters (Spatial) Laplacian
- Filters (Spatial) Local Normalization
- Filters (Spatial): Mean
- Filters (Spatial): Median
- Filters (Spatial): Mode
- Filters (Spatial): Nonlinear Noise Reduction
- Filters (Spatial): Nonmaximum Suppression
- Filters (Spatial): Regularized Isotropic (Nonlinear) Diffusion
- Filters (Spatial): Slice Averaging
- Filters (Spatial): Unsharp Mask
- Filters (Wavelet): Thresholding
- Fuzzy C-Means: Multispectral and Single Channel Algorithms
- Histogram Equalization: Regional Adaptive
- Histogram Equalization: Neighborhood Adaptive
- Histogram Matching
- 2D Histogram
- Histogram summary
- Manual 2D Series
- Extract Surface (Marching Cubes)
- Mask
- Microscopy Colocalization Orthogonal Regression
- Microscopy: Fluorescence Resonance Energy Transfer (FRET)-Acceptor
- Microscopy: FRAP (Fluorescence Recovery After Photobleaching)
- Microscopy: Blind Deconvolution
- Midsagittal line alignment
- Morphology
- Optimized automatic registration 3D
- Registration: Landmark-Least Squares
- Registration: Landmark-TPSpline
- Registration: Manual 2D Series
- Registration: Time Series Optimized Automatic Registration
- Reslice-Isotropic Voxels
- Shading Correction: Inhomogeneity N3 Correction
- Standard Deviation Threshold
- Subsampling images
- Threshold
- Transform to power of 2
Glossary
Appendices
Talairach
- Introduction
- Installing
- Mapping Brains in Talairach Space
- Task 1, Performing a semimanual transformation on datasets to the Talairach coordinate system
- Task 2, Applying Talairach VOIs
- Task 3, Segmenting the original image
- Task 4, Transforming Talairach image and Talairach VOIs-1 to the original image
- Task 5, Copying Talairach VOIs to segmented images
- Task 6, Calculating statistics on VOIs
- Viewing the Talairach grid on Talairach images
