3-D Volumetric Image Processing
Filter, segment, and perform other image processing operations on 3-D volumetric data
Perform pixel operations, local filtering, morphology, and other image processing, on 3-D data sets.
|Browse image slices (Since R2019b)|
|Browse orthogonal slices in grayscale or RGB volume (Since R2019b)|
|Extract oblique slice from 3-D volumetric data (Since R2020a)|
|Create 3-D viewer object (Since R2022b)|
|Display surface in 3-D viewer (Since R2022b)|
|Light source (Since R2023b)|
Image Import and Conversion
|Adaptive image threshold using local first-order statistics|
|Big or multiresolution image made from discrete blocks (Since R2021a)|
|Read DICOM image|
|Create 4-D volume from set of DICOM images|
|Extract ROI data from DICOM-RT structure set (Since R2020a)|
|Binarize 2-D grayscale image or 3-D volume by thresholding|
|Read metadata from NIfTI file|
|Write volume to file using NIfTI format|
|Read NIfTI image|
|Read volume or time series image stack from TIFF file (Since R2020b)|
Geometric Transformations and Image Registration
|Create output view for warping images (Since R2019b)|
|3-D affine geometric transformation (Since R2022b)|
|Crop 3-D image (Since R2019b)|
|Reference 3-D image to world coordinates|
|Intensity-based image registration|
|Estimate displacement field that aligns two 2-D or 3-D images|
|Resize 3-D volumetric intensity image|
|Rotate 3-D volumetric grayscale image|
|Apply geometric transformation to image|
|3-D rigid geometric transformation (Since R2022b)|
|3-D similarity geometric transformation (Since R2022b)|
|3-D translation geometric transformation (Since R2022b)|
|Apply forward geometric transformation|
|Apply inverse geometric transformation|
Image Filtering and Enhancement
|Enhance elongated or tubular structures in image using Frangi vesselness filter|
|Create predefined 3-D filter|
|Enhance contrast using histogram equalization|
|Adjust intensity values in N-D volumetric image|
|3-D box filtering of 3-D images|
|N-D filtering of multidimensional images|
|3-D Gaussian filtering of 3-D images|
|Adjust histogram of N-D image to match histogram of reference image|
|Add noise to image|
|3-D box filtering of 3-D integral images|
|Calculate 3-D integral image|
|3-D median filtering|
|Remove small objects from binary image|
|Find and count connected components in binary image|
|Morphological operations on binary volume|
|Reduce all objects to lines in 2-D binary image or 3-D binary volume|
|Morphologically close image|
|Morphologically open image|
|Morphological offset structuring element|
|Morphological structuring element|
|Segment image into foreground and background using active contours (snakes) region growing technique|
|Contour matching score for image segmentation|
|Sørensen-Dice similarity coefficient for image segmentation|
|Calculate weights for image pixels based on image gradient|
|Calculate weights for image pixels based on grayscale intensity difference|
|Binary image segmentation using fast marching method|
|K-means clustering based volume segmentation|
|Jaccard similarity coefficient for image segmentation|
|3-D superpixel oversegmentation of 3-D image|
Image Augmentation for Deep Learning
|Datastore for use with blocks from |
|Create cuboidal center cropping window (Since R2019b)|
|Create randomized cuboidal cropping window (Since R2019b)|
|Create randomized 3-D affine transformation (Since R2019b)|
|Datastore for extracting random 2-D or 3-D random patches from images or pixel label images|
- Explore 3-D Volumetric Data with Volume Viewer App
View perpendicular cross-sections of 3-D volumetric data and adjust the rendering to reveal structures within the volume.
- Explore 3-D Labeled Volumetric Data with Volume Viewer
View 3-D labeled volumetric data, and adjust the visualization such as the opacity and colormap, using the Volume Viewer app.
- Display Interior Labels by Clipping Volume Planes
Interactively clip a quadrant of a volumetric image to expose a surface within the volume.
- Display Interior Labels by Adjusting Volume Overlay Properties
Adjust the transparency of labeled volumetric data and the rendering style to reveal labels on the interior of the volume.
- Display Volume Using Cinematic Rendering
View volumes with photorealistic lighting and shadows using cinematic rendering.
- Display Translucent Volume with Advanced Light Scattering
This example shows how to display translucent volumes using realistic light scattering.
- Remove Objects from Volume Display Using 3-D Scissors
This example shows how to interactively remove unwanted regions in a 3-D display, such as a patient bed in a CT scan, by using 3-D scissors.
- Display Large 3-D Images Using Blocked Volume Visualization
This example shows how to display large 3-D image volumes using a
blockedImageobject and the
- Explore Slices from 3-D Image Volume with Anisotropic Voxel Spacing
Display slices from a 3-D image volume with voxel spacing that varies between spatial dimensions.
Process and Analyze Volumes
- Create Binary Mask Using Volume Segmenter
This example shows how to segment a volume in the Volume Segmenter app.
- Work with Blocked Images Using Volume Segmenter
Segment a volumetric image that could be too large to fit into memory by converting the volume to a blocked image.
- Compute 3-D Superpixels of Input Volumetric Intensity Image
Convert 3-D MRI data into a grayscale intensity image of superpixels.
- Preprocess Volumes for Deep Learning (Deep Learning Toolbox)
Read and preprocess volumetric image and label data for 3-D deep learning.