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Matlab Display Volume

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matlab
matlab-display-volume

Display 3-D image volumes, medical image volumes, surface meshes, and annotations for 3-D image processing. Use when displaying 3-D images or isosurfaces with volshow, creating volume viewers with viewer3d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming volumetric data, or building apps with volume display.

Overview

Publishermatlab
Repositorymatlab-agentic-toolkit
Skill namematlab-display-volume
Stars
1.2K
Forks
138
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by matlab on GitHub. Read the source before you install it.

Installation

Install the Matlab Display Volume AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/matlab/matlab-agentic-toolkit/tree/main/skills-catalog/image-processing-and-computer-vision/matlab-display-volume
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/matlab/matlab-agentic-toolkit.git /tmp/matlab-agentic-toolkit
mkdir -p .claude/skills
cp -r /tmp/matlab-agentic-toolkit/skills-catalog/image-processing-and-computer-vision/matlab-display-volume .claude/skills/matlab-display-volume
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Matlab Display Volume in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Matlab Display Volume on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Matlab Display Volume is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Volume Display

Display volumes with volshow for performant, high quality volume display. Display isosurface meshes, triangulations, and surfaces using images.ui.graphics.Surface rather than isosurface for more performant, higher quality mesh display with more responsive interactions for meshes of all sizes.

When to Use

  • User asks to create a GUI, app, dashboard, or interactive tool for volume, isosurface, or surface mesh display
  • User wants ROIs, annotations, or other lines and shapes plotted on top of the volume or surface mesh
  • User wants to display labeled data or other overlay volumes on top of a volume

When NOT to Use

  • User does not have the Image Processing Toolbox — fall back to isosurface + patch, but recommend volshow for better performance.

Medical Image Volumes

When the user has the Medical Imaging Toolbox, use medicalVolume to load DICOM/NIfTI/NRRD files, then call the volshow method on that object. This automatically sets the spatial Transformation and SpatialUnits from the file metadata. All other patterns in this skill (Viewer, overlays, annotations, streaming, app building) still apply — only the entry point differs.

matlab
medVol = medicalVolume("brain.nii");
obj = volshow(medVol);

Key Objects

ObjectConstructorKey callback
Viewerviewer3d(parent)CameraMovedFcn, ObjectClickedFcn
Volumevolshow(data, Parent=viewer)
Surfaceimages.ui.graphics.Surface(viewer, Data=tri)
Interactive Annotationsuidraw(parent, "shape")AnnotationMovedFcn (on Viewer)

Utilities: linkviewers(viewers) synchronizes camera motion across multiple Viewers. title(viewer, "text") sets the Viewer title.

Workflow

  1. Create Viewer — call viewer3d() or viewer3d(parent) for app contexts
  2. Add Volume — call volshow(V, Parent=viewer) to display volumetric data
  3. (Optional) Add surfaces — call images.ui.graphics.Surface(viewer, Data=tri) for mesh display
  4. (Optional) Add annotations — call uidraw(volObj, "line") for interactive ROIs
  5. (Optional) Configure callbacks — set CameraMovedFcn, AnnotationMovedFcn, or ObjectClickedFcn on the Viewer
  6. Update data — set obj.Data = newV to stream; use waitfor(viewer,"Busy",false) for synchronization

Legacy Patterns to Avoid

Do NOT useUse insteadWhy
isosurface + patchimages.ui.graphics.Surface(viewer, Data=tri)Better rendering, interactive performance, depth peeling
clear(viewer) then re-add objectsReuse objects, update Data propertyAvoids reconstruction overhead
drawnow for volume streaming syncwaitfor(viewer,"Busy",false)Volume data loads asynchronously; drawnow is still appropriate for Surface animation
Creating new volshow each frameKeep reference, set obj.Data = VReuse avoids GPU reallocation

Patterns

Standard Volume Display

Simple cases of volume display can call volshow without specifying a parent. All name-value arguments can be set as properties on the Volume object, and the volume data can be updated by setting the Data property.

matlab
obj = volshow(V);

Choose DisplayRangeMode based on the data type and value range:

Data characteristicsRecommended mode
Normalized single/double in [0, 1]"data-range" (default)
uint8 or int8"data-range" (default)
uint16 with values up to 1023 (e.g., 10-bit CT)"10-bit"
uint16 with values up to 4095 (e.g., 12-bit CT/MR)"12-bit"
uint16 full range or int16"16-bit"
Custom window/level needed"manual" with DisplayRange=[low high]
matlab
% 12-bit medical volume
obj = volshow(V, DisplayRangeMode="12-bit");

% Manual window/level
obj = volshow(V, DisplayRangeMode="manual", DisplayRange=[200 1200]);

Set RenderingStyle to control how voxel data is visualized. See the dedicated Rendering Styles section below for detailed guidance.

Choosing a Colormap — Select based on data content:

Data contentRecommended colormapRationale
CT / MR (anatomical)gray(256)Clinical convention; preserves radiologist familiarity
CT with window/levelgray(256) + DisplayRangeNarrow range highlights target tissue
Fluorescence / emissionhot(256) or green(256)Hot emphasizes intensity peaks; green matches fluorophore
General scientificparula(256) (default)Perceptually uniform, accessible
Multi-structure / labeledturbo(256)Full-spectrum rainbow, perceptually ordered
Signed data (e.g., flow, strain)Custom diverging (blue-white-red)Distinguishes positive/negative around midpoint
matlab
obj = volshow(V, Colormap=gray(256));

Choosing an Alphamap — The alphamap is a 256×1 vector mapping normalized intensity [0, 1] to opacity [0, 1]. It controls which structures are visible vs. transparent. The default is a cubic ramp (x.^3), which suppresses low-intensity background while revealing bright structures.

GoalAlphamap shapeConstruction
Show bright structures, hide backgroundCubic ramp (default)linspace(0,1,256)'.^3
Show all intensities equallyLinear ramplinspace(0,1,256)'
Reveal only a specific intensity bandGaussian peakexp(-((x-center).^2)/(2*width^2))
Hard threshold (binary visibility)Step functiondouble((1:256)' > threshold)
Hide bright, show dim (e.g., cavities)Inverted ramplinspace(1,0,256)'
Custom: show bone, hide soft tissue (CT)Step at bone HUdouble(linspace(0,1,256)' > 0.3)
matlab
% Gaussian alphamap centered at 60% intensity (width 10%)
x = linspace(0, 1, 256)';
alpha = exp(-((x - 0.6).^2) / (2*0.1^2));
obj = volshow(V, Alphamap=alpha, Colormap=gray(256));

% Hard threshold — only show voxels above 30% of the display range
alpha = double(linspace(0, 1, 256)' > 0.3);
obj = volshow(V, Alphamap=alpha);

For per-voxel opacity control (e.g., masking specific regions regardless of intensity), set the AlphaData property to a volume the same size as Data with values in [0, 1]:

matlab
obj = volshow(V, AlphaData=double(regionMask));

When displaying an overlay of a mask, semantic segmentation, or other volume data on top of another volume, use the OverlayData property of the Volume object and the corresponding name-value arguments OverlayColormap, OverlayAlpha, OverlayRenderingStyle, OverlayDisplayRange, and OverlayDisplayRangeMode to adjust the overlay display. This is a faster option than blending the overlay with the volume and updating the Data property, or adding a second Volume object to the Viewer. The default properties for overlay display are tuned to support semantic labels, but can be adjusted to support continuous data for other purposes.

matlab
obj = volshow(V, OverlayData=mask);

If spatial referencing information is available, include it in the Transformation name-value argument. Build an imref3d from voxel spacing and volume size, or use an affinetform3d for arbitrary affine transforms. When using medicalVolume, the volshow method sets the transformation automatically from file metadata.

matlab
% From voxel spacing (e.g., [0.5 0.5 1.0] mm)
R = imref3d(size(V), 0.5, 0.5, 1.0);
obj = volshow(V, Transformation=R);

% From an affine matrix
tform = affinetform3d(A);
obj = volshow(V, Transformation=tform);

For large volumes that exceed GPU texture memory (typically > 2048³ voxels) or are too large to fit in RAM, create a multilevel blockedImage and pass it to volshow. The makeMultiLevel3D function creates a resolution pyramid for progressive rendering — the Viewer loads coarse levels first, then refines as the camera settles.

matlab
bim = blockedImage(V, BlockSize=[512,512,512]);
mbim = makeMultiLevel3D(bim, Scales=[2 4 8]);
volshow(mbim);

Use Scales to control the downsampling factors. Each scale creates a level at 1/N resolution. For very large volumes (e.g., 4096³+), include more scales (e.g., [2 4 8 16]). Smaller volumes that just exceed the texture limit need fewer levels (e.g., [2 4]). The BlockSize should match or be a multiple of the GPU texture block size (512³ is a good default).

Surface Mesh Display

Displaying surface meshes using images.ui.graphics.Surface offers better rendering and interactive performance over isosurface + patch. Pass a triangulation object as Data and an N×3 matrix of per-vertex RGB colors as Color.

matlab
% tri = triangulation(...), cpoints = N-by-3 vertex colors
viewer = viewer3d(BackgroundGradient="off", BackgroundColor="white");
obj = images.ui.graphics.Surface(viewer, Data=tri, Color=cpoints);

When possible, displaying the mesh with the default Alpha of 1.0 is recommended for optimal performance. You can call images.ui.graphics.Surface multiple times to add multiple objects to the scene and the objects will be sorted and rendered spatially correct with depth peeling. When objects are transparent, more render passes are required and the performance will decrease.

Surface meshes can be displayed together with volumes in the same Viewer.

matlab
viewer = viewer3d();
volObj = volshow(V, Parent=viewer);
surfObj = images.ui.graphics.Surface(viewer, Data=tri);

When updating the position or size of a Surface, it is much faster to update the Transformation property than to re-set Data with a new triangulation. Use drawnow to flush the graphics queue between frames (this is appropriate for Surface animation — only volume streaming requires waitfor).

matlab
viewer = viewer3d(BackgroundGradient="off", BackgroundColor="white");
obj = images.ui.graphics.Surface(viewer, Data=tri, Color=cpoints);

% Disable auto camera position update
viewer.CameraPositionMode = "manual";

% Animate the surface moving in the z direction
for idx = 1:100
    tform = transltform3d(0, 0, idx);
    obj.Transformation = tform;
    drawnow;
end

Rendering Styles

The RenderingStyle property on the Volume object controls how voxel data is visualized. Choose the style based on what structures need to be visible.

Maximum Intensity Projection (MIP) — Projects the brightest voxel along each viewing ray onto the screen. Ideal for vascular imaging (angiography), fluorescence microscopy, or any data where bright structures are the signal of interest.

matlab
obj = volshow(V, RenderingStyle="MaximumIntensityProjection");

Gradient Opacity — Makes large homogeneous regions (low gradient) transparent while preserving regions with sharp intensity transitions (high gradient). This lets you see through bulk tissue to reveal boundaries and edges within the volume.

matlab
obj = volshow(V, RenderingStyle="GradientOpacity");

Cinematic Rendering — State-of-the-art photorealistic rendering with global illumination, ambient occlusion, and soft shadows. Produces the highest quality visualization for solid structures like bone in CT scans. More computationally expensive but delivers publication-quality results.

matlab
obj = volshow(V, RenderingStyle="CinematicRendering");

Other styles:

RenderingStyleUse when
"VolumeRendering"Default — semi-transparent volume with transfer function based on intensity
"MinimumIntensityProjection"Showing darkest structures (e.g., airways, cavities)
"Isosurface"Displaying a surface at a threshold (set IsosurfaceValue)
"SlicePlanes"Viewing orthogonal slices through the volume
"LightScattering"Simulated light scattering for soft tissue appearance
matlab
% Isosurface at a specific threshold (e.g., bone in CT)
obj = volshow(V, RenderingStyle="Isosurface", IsosurfaceValue=300);

% Orthogonal slice planes
obj = volshow(V, RenderingStyle="SlicePlanes");

Streaming Volumes

When updating the display, reuse objects whenever possible. Avoid using the clear method on the Viewer when you are going to re-add the same types of objects — always reuse. Keep the Volume object returned by volshow and update its Data property. Volume data is loaded asynchronously, so drawnow may return before rendering completes. Use waitfor on the Viewer's Busy property to block until the data has finished loading.

matlab
viewer = viewer3d();
obj = volshow([], Parent=viewer);

for idx = 1:10
    V = rand([512,512,512]);
    obj.Data = V;
    waitfor(viewer, "Busy", false);
end

Generating Animations

When generating animations or capturing frames, use getframe and pass the Viewer (parent of the Volume object) as the first argument. The Viewer waits until all pending updates have processed before capturing, which guarantees each frame is fully rendered.

matlab
viewer = viewer3d();
obj = volshow([], Parent=viewer);

frames = cell(1, 100);
for idx = 1:100
    V = rand([512,512,512]);
    obj.Data = V;
    frames{idx} = getframe(viewer);
end

Adding Annotations on Volume

When displaying interactive or a small number of annotations on the volume, use the uidraw function to start interactively drawing or to programmatically place an annotation.

uidraw is ideal for fewer than 100 annotations. Omitting Position starts interactive drawing. When Label is not specified, the ROI displays a standard measurement (e.g., distance for lines). Set SpatialUnits on the Viewer to include units in the measurement display.

matlab
obj = volshow(V);
viewer = obj.Parent;
viewer.SpatialUnits = "mm";

% Interactive drawing (user places the line)
roi = uidraw(obj, "line", Color=[1,0,0]);

% Programmatic placement (no interaction required)
roi2 = uidraw(obj, "point", Position=[20,20,50], Color=[0,0,1], Label="Point of Interest");

% Multi-point polyline from a position matrix (each row is a point)
pos = [20,20,50; 50,60,75; 50,80,100];
roi3 = uidraw(obj, "polyline", Position=pos, Color=[0,1,0]);

% Make an annotation static (disable further interaction)
set(roi3, "Interactions", "none");

Responding to User Interactivity

Add function handles to callback properties on the Viewer to respond to user interaction. CameraMovedFcn fires after the camera is moved. AnnotationMovedFcn fires after the user interactively moves or reshapes an annotation. ObjectClickedFcn fires after the user clicks and releases in the Viewer without dragging (a click-and-drag initiates the default interaction, typically panning). Use the event data to determine which object was clicked.

matlab
V = rand([100,100,100]);
obj = volshow(V);
viewer = obj.Parent;
% Draw a rectangle ROI interactively
roi = uidraw(obj, "point", Color=[0,1,0], Label="ROI");
% Listen for movement and display the position
viewer.AnnotationMovedFcn = @(~,evt) fprintf("ROI Position: [%.1f, %.1f, %.1f]\n", evt.Position);

App Building

When building apps, call viewer3d(parent) to create a Viewer parented to a uigridlayout, then call volshow with that Viewer as the parent. Create the Volume object eagerly at construction time with empty data ([]) — this avoids conditional logic later and lets you simply update obj.Data when data becomes available. Only defer Volume creation if the app supports switching between fundamentally different display modes (e.g., volume vs. surface-only).

Use a standard app classdef (see matlab-build-app skill) with the following in createComponents:

matlab
% Inside createComponents(app) — viewer3d parented to grid layout
app.GridLayout = uigridlayout(app.UIFigure, [1 1]);
app.GridLayout.RowHeight = {"fit"};
app.GridLayout.ColumnWidth = {"fit"};

app.Viewer = viewer3d(app.GridLayout);
title(app.Viewer, "App Display");
app.Viewer.Layout.Row = 1;
app.Viewer.Layout.Column = 1;

% Create Volume eagerly with empty data
app.Volume = volshow([], Parent=app.Viewer);

Then update data later with app.Volume.Data = im;.

Adding a Colorbar to a Volume App

Since the Viewer does not natively support a colorbar, place an invisible uiaxes with a colorbar in an adjacent grid column. Set Colormap and CLim on the axes to match the Volume object, then call colorbar on that axes.

matlab
fig = uifigure(Name="Volume with Colorbar", Position=[100 100 800 500]);
gl = uigridlayout(fig, [1 2]);
gl.ColumnWidth = {"1x", 80};

% Volume viewer in left column
viewer = viewer3d(gl);
viewer.Layout.Row = 1;
viewer.Layout.Column = 1;
title(viewer, "Colorbar with Volshow");

V = rand([64 64 64]);
vol = volshow(V, Parent=viewer, Colormap=parula(256));

% Invisible axes with colorbar in right column
ax = uiaxes(gl, Visible="off", HitTest="off", PickableParts="none");
ax.Layout.Row = 1;
ax.Layout.Column = 2;
ax.Toolbar.Visible = "off";

% Match colormap and data range to the Volume object
ax.Colormap = vol.Colormap;
ax.CLim = [min(vol.Data, [], "all"), max(vol.Data, [], "all")];
cb = colorbar(ax, Units="normalized");

Linking Multiple Viewers

Use linkviewers to synchronize camera motion across multiple Viewers. When the user rotates or zooms one Viewer, all linked Viewers update to match. Pass "off" to unlink.

matlab
viewer1 = viewer3d();
viewer2 = viewer3d();
title(viewer1, "Original");
title(viewer2, "Segmentation");

volshow(V, Parent=viewer1);
volshow(V, Parent=viewer2, OverlayData=mask);

linkviewers([viewer1, viewer2]);

Conventions

  • Always: Pass the Viewer as the first positional argument to images.ui.graphics.Surface(viewer, ...) — do NOT use Parent=viewer as a name-value argument
  • Always: Reuse Volume objects by updating obj.Data — never recreate the volume each frame
  • Always: Use waitfor(viewer, "Busy", false) to synchronize after setting Data when timing matters (screenshots, frame capture)
  • Always: Use getframe(viewer) not getframe(gcf) for screenshots — the Viewer handles async completion
  • Always: When the user has Medical Imaging Toolbox, use volshow(medVol) on a medicalVolume object — this auto-sets Transformation and SpatialUnits
  • Never: Call clear(viewer) to reset the scene — reuse existing objects instead
  • Never: Use isosurface + patch for mesh display when Image Processing Toolbox is available
  • Prefer: OverlayData property for masks/segmentations over blending into Data or adding a second volume
  • Prefer: Updating Transformation over re-setting Data when only position/size changes

Copyright 2026 The MathWorks, Inc.


Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Matlab Display Volume AI skill do?

Display 3-D image volumes, medical image volumes, surface meshes, and annotations for 3-D image processing. Use when displaying 3-D images or isosurfaces with volshow, creating volume viewers with viewer3d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming volumetric data, or building apps with volume display.

Why use Matlab Display Volume on TypingMind?

Because you install it once and use it with any model. Matlab Display Volume is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Matlab Display Volume in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/matlab/matlab-agentic-toolkit/tree/main/skills-catalog/image-processing-and-computer-vision/matlab-display-volume. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Matlab Display Volume?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Matlab Display Volume?

As many as you like. As long as a model supports skills, you can use Matlab Display Volume with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Matlab Display Volume AI skill free?

It is published on GitHub by matlab. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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