Matlab Process Images
MathWorksOfficialCreated by MathWorks
- Skill
- Tool integration
- Software development
- BSD-2-Clause
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill serves as the primary entry point for MATLAB tasks involving images, scans, frames, and 3-D volumes. It provides core conventions for image data types, coordinate systems, and display practices, while routing users to specific references for tasks such as I/O, filtering, segmentation, and measurement. It ensures consistent use of Image Processing Toolbox functions and helps users navigate common pitfalls in image analysis workflows.
What it does
- Provides standardized conventions for image data types and coordinate systems.
- Routes users to specialized references for image I/O, filtering, and transformation tasks.
- Defines best practices for displaying images using the imageshow function.
- Offers guidance on handling 3-D volumetric data and large-scale images.
- Assists with selecting appropriate functions for segmentation and object measurement.
- Provides troubleshooting patterns for common image processing errors.
When to use it
- When performing image processing tasks in MATLAB, such as filtering, enhancing, or segmenting.
- When working with image formats like TIFF, PNG, JPEG, DICOM, or NIfTI.
- When needing to understand MATLAB-specific coordinate conventions for image data.
- When determining the correct toolbox function for a specific image analysis goal.
- When troubleshooting syntax or type-related errors in image processing scripts.
Advantages
- Ensures consistent coding patterns across different image processing tasks.
- Reduces errors by providing clear guidance on coordinate and data type conventions.
- Simplifies the selection of appropriate tools for complex workflows like 3-D volume processing.
- Promotes the use of modern display functions like imageshow over legacy alternatives.
- Provides a structured approach to identifying the correct documentation for specific functions.
Usage examples
- “How do I read a DICOM file and display it in MATLAB?”
- The agent will guide you to use the medical-data-io reference for reading the file and the imageshow function for display, following the core conventions.
- “I need to count the number of objects in a binary image.”
- The agent will provide the standard analysis pipeline using bwconncomp and regionprops, ensuring the input is correctly formatted as logical.
- “How do I perform 3-D filtering on a volume?”
- The agent will direct you to the 3-D volume processing reference to select the appropriate 3-D specific function, such as imgaussfilt3.
- “Why is my regionprops measurement returning only one object?”
- The agent will explain that the input must be a logical array and provide the code to convert your numeric array to logical.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/matlab/matlab-process-images/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip matlab-process-images.zip -d .agents/skills
Documentation by MathWorks
Image Processing
Process, analyze, and transform images using MATLAB Image Processing Toolbox (IPT). This skill routes you to the correct reference for your task and provides core conventions that apply across all IPT work.
When to Use
Loaded for general-purpose IPT work: file and batch I/O, filtering, restoration, morphology, segmentation, measurement, geometric transforms, color, texture, quality metrics, deep learning on images, and image apps. Non-medical microscopy — cell and particle counting on plain IPT — is in scope.
Hand off (and co-load) instead of answering alone: see the handoff table under ## Routing.
When NOT to Use
Training a network with no image-specific preprocessing — use Deep Learning Toolbox directly
Simulink or Stateflow video blocks — use Simulink directly
C/C++ code generation, MEX, GPU acceleration and deployment — use MATLAB Coder / GPU Coder directly
Point clouds, 3-D reconstruction, and video stabilization — use Computer Vision Toolbox directly
General MATLAB questions unrelated to images
Looking at an image yourself (e.g., "look at this screenshot") when no MATLAB work is requested — use your own vision instead
Core Conventions
Image Data Types
| Type | Range | When to use |
|---|---|---|
uint8 | 0–255 | Display, file I/O, memory-efficient storage |
uint16 | 0–65535 | High dynamic range sensors, medical. Camera RAW is n-bit in a uint16 container — rescale with rawinfo BlackLevel/WhiteLevel, not 65535 |
single / double | 0.0–1.0 | Arithmetic, filtering, computation |
logical | 0 or 1 | Binary masks, segmentation results |
Most IPT functions accept integer types directly — do not convert to floating-point unless required.
Default Coordinate Conventions
MATLAB images are (row, col) — row is Y (down), column is X (right)
size(img)returns[height, width, channels]Spatial functions use (x, y) order for coordinates (e.g.,
imref2d,regionpropscentroids)Pixel centers are at integer intrinsic coordinates; in default world referencing, pixel (1,1) center is at world (1.0, 1.0) and the image edge starts at 0.5
imref2dandimref3dcan specify non-default spatial referencing to place images into world coordinate systems. By default they use the unit-spaced, integer-pixel-centered coordinate system described here, e.g.Rout = imref2d(imageSize). Functions that do not accept spatial referencing objects assume this intrinsic coordinate system for any operation requiring spatial referencing.
Multichannel Images
Grayscale:
M×NorM×N×1RGB:
M×N×3With alpha: read using
[img, ~, alpha] = imread(...)(alpha is the third output)Convert:
rgb2gray,im2gray(preferred, handles more input types)
Display Functions — use imageshow, not imshow
Always use imageshow instead of imshow in all generated code — scripts, apps, examples, and quick previews. The signatures are compatible for common cases: replace imshow(...) with imageshow(...). imageshow (R2024b+) handles sub-bit-depth containers (e.g., 12-bit in uint16) via DisplayRangeMode, supports OverlayData for label/mask overlays, and works with viewer2d. imshow lacks all of these capabilities and should not appear in new code.
Title convention: imageshow creates a viewer2d, not an axes — gca does not return it. To add a title, get the viewer from the Image object's parent:
obj = imageshow(im);
viewer = obj.Parent;
title(viewer, "Title Text");Do not use title("text") or title(gca, "text") after imageshow — these silently fail or create a stray axes title.
Code Execution
Execute code blocks via evaluate_matlab_code before presenting them to the user. If it errors, fix and re-run. This catches type mismatches, wrong argument orders, and nonexistent functions before the user sees them. If execution requires user data or toolboxes not available in the current session, present the code with a note that it should be run with the user's own data — do not loop trying to synthesize stand-in data.
Error Recovery
If code throws an error after execution, load the matlab-read-documentation skill and look up the function's doc page to verify syntax, required arguments, and supported input types before retrying.
When to Ask the User
Ask for clarification before proceeding when:
The image type/format is ambiguous and affects the processing approach
Multiple valid approaches exist with different tradeoffs (speed vs quality, lossy vs lossless)
The task requires choosing parameters that depend on domain knowledge (e.g., object size thresholds, noise characteristics)
The user's MATLAB release is unknown and the recommended function may not be available
Routing
Match your task in the tables below. Check the handoff table first. If the task belongs to another skill, load that skill in addition to this one — the Core Conventions above (data types, coordinate order, code execution) apply to all image data. Do not re-derive them from the sibling. If a row in both tables fits, the handoff table wins on workflow; this skill still owns conventions.
Unfamiliar data? Load
references/image-understanding.mdfirst — but only when class, range, or content is unknown.Starting from a function name, not a task? The function column is illustrative, not exhaustive. To locate any function:
grep -rln '<functionName>' references/. To look up syntax details, loadmatlab-read-documentation.Pipeline tasks: load several references; cap at three unless the task genuinely spans more.
Follow the patterns in loaded references. References contain specific code patterns and workflows — use them instead of improvising equivalent code from general knowledge.
No row matches? Name the owning product, state the closest IPT fallback, and say so — do not guess a reference.
Check first: is this another skill's job?
| If the task involves... | Also load |
|---|---|
| Segmenting anatomy — tumor, lesion, organ, vessel — in CT, MRI, PET, ultrasound; MedSAM; radiomics | No skill covers this — Medical Imaging Toolbox (segmentMedicalImage, groundTruthMedical); look up the doc page |
Displaying or viewing a 2-D image: imshow, imageshow, viewer2d, montage, mask overlay, annotation, colorbar, colormap, figure export | matlab-display-image |
Displaying a 3-D volume: volshow, viewer3d, isosurface rendering, slice viewer, orthogonal views | matlab-display-volume |
| Hyperspectral or multispectral cubes, spectral indices, unmixing, ENVI, band selection | matlab-analyze-spectral-images |
| Calling a PyTorch or ONNX vision model from MATLAB | matlab-integrate-pytorch-vision |
| OCR, text recognition, reading text out of an image | matlab-recognize-text (requires Computer Vision Toolbox) |
| Factory-floor visual inspection: anomaly detection, defect/scratch/dent detection, gauging, pass/fail counting | matlab-use-visual-inspection (requires Visual Inspection Toolbox, R2026b+) |
| Barcode or QR reading, camera calibration | No skill covers this — Computer Vision Toolbox (readBarcode, estimateCameraParameters); look up the doc page |
| Optical system design: lens import, prescription-side MTF, spot diagrams, ray tracing, tolerance analysis | matlab-model-optics |
In scope: pick the reference
| If the task or the user's words involve... | Illustrative functions | Load |
|---|---|---|
| inspect, understand, characterize, explore data, look at my images, what kind of image, what am I working with, what's in this folder, describe the data, summarize the dataset, what format, bit depth, class and range, indexed image, alpha channel, metadata, file info, dataset characterization, before I start processing | imfinfo, imhist, countEachLabel | references/image-understanding.md |
| read, write, load, save, import, export, open an image, convert format, batch, folder of images, TIFF, PNG, JPEG, RAW, HDR, test pattern | imread, imwrite, imageDatastore, hdrread | references/image-io.md |
| video, footage, frames, read video, write video, VideoReader, VideoWriter, frame rate, video codec, MP4, AVI | VideoReader, VideoWriter, readFrame, hasFrame, writeVideo | references/video-io.md |
| smooth, blur an image, sharpen, denoise, noise, grainy, filter, kernel, padding, edge-preserving, bilateral, non-local means, frequency filter | imgaussfilt, medfilt2, imsharpen, imbilatfilt, imnlmfilt, imdiffusefilt, imfilter, ordfilt2, locallapfilt, wiener2 | references/filtering.md |
| contrast, brighten, darken, too dark, washed out, enhance, improve, histogram, equalize, CLAHE, normalize, rescale, blend, arithmetic, type convert, flat-field, illumination correction, vignetting, uneven lighting | imadjust, stretchlim, adapthisteq, histeq, rescale, mat2gray, im2single, imadd, imlincomb, imblend, imflatfield | references/preprocessing.md |
| erode, dilate, open, close, structuring element, 2-D morphology, fill holes, remove small objects, skeletonize, thin, tidy up a binary result | strel, imerode, imdilate, imopen, imclose, imfill, bwareaopen, bwskel, imtophat, imreconstruct | references/morphological-ops.md |
| deblur, blurry, unfocused, out of focus, motion blur, camera shake, restore a blurred image, deconvolution, PSF estimation | deconvblind, deconvlucy, deconvwnr, deconvreg | references/deblurring.md |
| resize, rotate, crop, warp, scale, flip, straighten, affine, projective, perspective, undistort, lens distortion, spatial referencing, world coordinates, voxel coordinates, pixel coordinates, coordinate conversion | imresize, imrotate, imcrop, imwarp, imtranslate, affinetform2d, imref2d | references/geometric-transforms.md |
| align two images, stitch, mosaic, panorama, overlapping shots, seam, motion correction, multi-modal alignment, control points, non-rigid, deformable, homography (feature-based requires Computer Vision Toolbox) | imregister, imregtform, imregdemons, imregcorr, detectSIFTFeatures, matchFeatures, estgeotform2d (last three: Computer Vision Toolbox), imregdeform (Medical Imaging Toolbox) | references/registration.md |
segment or threshold with no user input: binarize, Otsu, watershed, k-means or colour clustering, imsegsam automatic mode, deep-learning segmentation | imbinarize, graythresh, multithresh, adaptthresh, watershed, imsegkmeans, imsegkmeans3, imsegisodata, imsegsam | references/segmentation-automated.md |
| segment with user input: clicks, points, boxes, scribbles, seeds, prompted SAM, grabcut, active contours, region growing, lazy snapping, superpixels, App Designer segmentation UIs | segmentAnythingModel, grabcut, activecontour, lazysnapping, imsegfmm, grayconnected, superpixels | references/segmentation-interactive.md |
| measure, count objects, how many, area, perimeter, centroid, size, shape, width, thickness, gap, diameter, Feret, orientation, detect edges, circles, lines, boundary tracing, ROI, world units, metrology, region, region properties, analysis | regionprops, bwconncomp, bwareafilt, bwpropfilt, bwlabel, edge, imfindcircles, hough, bwboundaries | references/analysis-measurement.md |
| quality, PSNR, SSIM, sharpness, noise level, is it blurry, compare two images, difference, before/after, MTF (camera/chart SFR), test chart, artifact (register first — full-reference metrics need pixel correspondence) | psnr, ssim, multissim, immse, brisque, niqe, piqe, measureSharpness, esfrChart | references/quality-assessment.md |
| texture, repetitive pattern, frequency domain, Fourier, FFT, DCT, Radon, Gabor, co-occurrence, GLCM | graycomatrix, graycoprops, entropyfilt, fft2, dct2, radon, gabor | references/texture-transforms.md |
| color space, LAB, HSV, hue, saturation, white balance, color cast, color correction, color balance, ICC profile, grayscale conversion | rgb2lab, lab2rgb, rgb2hsv, chromadapt, illumwhite, makecform, deltaE, decorrstretch | references/color-processing.md |
| 3-D array, volume, volumetric, voxel, slice stack, z-stack — filtering, 3-D morphology, 3-D transforms, or measurement applied to a volume | imgaussfilt3, medfilt3, imresize3, regionprops3, bwvolumefilt (R2026b), bwpropfilt3 (R2026b) | references/3d-volume-processing.md |
| deep learning, neural network, train, U-Net, semantic segmentation networks, classify images, pretrained model, transfer learning, fine-tune, inference, augment, training dataset (requires DLT, often CVT) | unet, deeplabv3plus, trainnet, semanticseg, imageDataAugmenter, augmentedImageDatastore | references/deep-learning-imaging.md |
| build your own image app or GUI: sliders, live preview, parameter tuning, ROI widgets | uifigure, uigridlayout, uislider, drawrectangle | references/app-building.md |
DICOM, NIfTI, NRRD, DICOM-RT, patient metadata, anonymizing, medicalVolume, medicalImage, reading/writing medical formats, extractSlice, volume orientation, medical spatial referencing | medicalVolume, medicalImage, dicomreadVolume, dicomCollection, extractSlice, dicomContours, dicomanon | references/medical-data-io.md |
gigapixel, whole-slide, out-of-memory images, blockedImage, tiled workflows, image pyramids, .svs, .ndpi, .czi, TIFF > 10,000 px, parallel image processing, custom adapters | blockedImage, apply, getBlock, getRegion, selectBlockLocations, blockedImageDatastore | references/large-image-processing.md |
Toolbox Detection
When unsure what's available, check installed toolboxes:
hasIPT = ~isempty(ver('images'));
hasCVT = ~isempty(ver('vision'));
hasDLT = ~isempty(ver('nnet'));
hasMIT = ~isempty(ver('medical'));
hasWavelet = ~isempty(ver('wavelet'));Most functions in this skill require Image Processing Toolbox. The deep-learning-imaging reference also requires Deep Learning Toolbox. Feature-based registration (detectSIFTFeatures, matchFeatures, estgeotform2d) requires Computer Vision Toolbox.
Release-Gated Features
This skill targets R2024b+ but some features require newer releases. References annotate these with the required release. Key ones:
R2024b:
imageshow,imblend,viewer2dR2026a:
uidraw,uipaint,linkviewersR2026b:
bwvolumefilt,bwpropfilt3,uiannotate
If targeting an older release, check with isMATLABReleaseOlderThan("R2026a") and use the fallback patterns documented in the references. To check release notes for a specific function, load matlab-read-documentation.
Copyright 2026 The MathWorks, Inc.
Files
- ATTRIBUTION.mdAdded by AutoGineer1.1 KiB
- LICENSELicence file added by AutoGineer1.4 KiB
- SKILL.md15.8 KiB
- manifest.yaml811 B
- references/3d-volume-processing.md20.2 KiB
- references/analysis-measurement.md18.5 KiB
- references/app-building.md16.9 KiB
- references/blocked-3d-volumes.md9.9 KiB
- references/blocked-data-discovery.md22.1 KiB
- references/blocked-geospatial.md3.2 KiB
- references/blocked-specialized-workflows.md4.3 KiB
- references/blocked-training-and-labeling.md7.0 KiB
- references/blocked-visualization.md5.1 KiB
- references/blocked-whole-slide-images.md3.1 KiB
- references/color-processing.md9.0 KiB
- references/deblurring.md8.1 KiB
- references/deep-learning-imaging.md14.8 KiB
- references/dicom-anonymization.md3.3 KiB
- references/dicom-rt-workflows.md7.4 KiB
- references/filtering.md21.8 KiB
- references/geometric-transforms.md14.3 KiB
- references/image-io.md15.5 KiB
- references/image-understanding.md20.0 KiB
- references/ipt-reading-writing.md4.8 KiB
- references/large-image-processing.md12.3 KiB
- references/medical-data-io.md8.3 KiB
- references/mit-medical-volume.md8.2 KiB
- references/mit-spatial-referencing.md5.9 KiB
- references/morphological-ops.md18.0 KiB
- references/preprocessing.md14.4 KiB
- references/quality-assessment.md13.5 KiB
- references/registration.md24.7 KiB
- references/segmentation-automated.md9.7 KiB
- references/segmentation-interactive.md15.3 KiB
- references/texture-transforms.md10.4 KiB
- references/video-io.md3.4 KiB
references/medical-data-io.md
Read and Write Medical Data
Read, write, and manipulate medical imaging data in MATLAB. This reference covers both Image Processing Toolbox (IPT) functions and Medical Imaging Toolbox (MIT) enhanced APIs.
When to Use
Reading or writing DICOM, NIfTI, or NRRD files
Listing DICOM series with
dicomCollectionExtracting spatial referencing or coordinate transforms
Changing volume orientation or extracting oriented slices
Working with DICOM RT structures (contours, masks, modify/write)
Anonymizing DICOM data
Toolbox Detection — CRITICAL FIRST STEP
Always check which toolboxes are available before choosing an approach. If Medical Imaging Toolbox is installed, prefer its APIs. If only Image Processing Toolbox is available, use IPT patterns.
Task → Function Quick Reference
| Task | IPT only | With Medical Imaging Toolbox (preferred) |
|---|---|---|
| Read single DICOM file | dicomread + dicominfo | medicalImage |
| Read DICOM folder | dicomreadVolume | medicalVolume |
| Read NIfTI | niftiread + niftiinfo | medicalVolume |
| Read NRRD | — (requires MIT) | medicalVolume or nrrdread + nrrdinfo |
| List DICOM series | dicomCollection | dicomCollection |
| Spatial referencing | imref3d | medicalref3d |
| Extract oriented slice | Manual indexing | extractSlice |
| Change orientation | Manual permute | updateOrientation |
| Read DICOM RT structure | dicomContours(dicominfo(file)) | Same |
| Anonymize DICOM | dicomanon + dicomuid | Same |
| Visualize volume | volumeViewer | medicalVolumeViewer or volshow(medVol) |
Top 4 Patterns
1. Read DICOM folder
Call medicalVolume or dicomreadVolume directly on the DICOM folder path. Do NOT call dicomCollection first — it is unnecessary when reading a single-series folder.
% WITH Medical Imaging Toolbox (preferred):
medVol = medicalVolume("path/to/dicom/folder");
V = medVol.Voxels; % Auto-rescaled (e.g., HU for CT)
spacing = medVol.VoxelSpacing; % [row col slice] in mm (note: constructor takes [x y z] but property returns [row col slice])
orientation = medVol.Orientation; % "transverse", "coronal", "sagittal"
modality = medVol.Modality; % "CT", "MR"
% Access spatial referencing via VolumeGeometry (medicalref3d object)
geom = medVol.VolumeGeometry;
geom.VolumeSize; % [rows cols slices]
geom.PatientCoordinateSystem; % "LPS+" or "RAS+"
geom.Position; % [slices×3] slice positions in patient coords
geom.VoxelDistances; % {[slices×3] [slices×3] [slices×3]} per-axis distances
geom.PixelSpacing; % [slices×2] in-plane pixel spacing per slice
geom.IsAffine; % true if uniform spacing (affine transform)
geom.IsAxesAligned; % true if volume axes align with patient axes
geom.IsMixed; % true if slices have varying pixel spacing
% IPT only:
[V, spatial, dim] = dicomreadVolume("path/to/dicom/folder");
V = squeeze(V); % Remove singleton 4th dimension2. Read NIfTI file
% WITH Medical Imaging Toolbox (preferred):
medVol = medicalVolume("path/to/file.nii.gz");
% IPT only:
V = niftiread("path/to/file.nii.gz");
info = niftiinfo("path/to/file.nii.gz");
voxelSize = info.PixelDimensions(1:3);3. List DICOM series and read one
Use dicomCollection only when:
The user says the folder contains multiple series or volumes
medicalVolumeordicomreadVolumefails with an error (e.g., "not a DICOM file" or "multiple volumes detected")You need to identify what series exist before deciding which one to read
dicomCollection scans the directory, excludes non-DICOM files, and returns a table where each row is one series. It does not read pixel data.
collection = dicomCollection("path/to/directory");
disp(collection); % Table with Modality, SeriesDescription, Rows, Columns, Frames
% WITH Medical Imaging Toolbox:
medVol = medicalVolume(collection, "s1");
% IPT only:
[V, spatial] = dicomreadVolume(collection, "s1");4. Extract slice / change orientation (Requires Medical Imaging Toolbox)
medVol = medicalVolume("path/to/file.nii");
% Extract slices — works for any orientation
[axialSlice, position, spacings] = extractSlice(medVol, 50, "transverse");
[coronalSlice, ~, ~] = extractSlice(medVol, 30, "coronal");
[sagittalSlice, ~, ~] = extractSlice(medVol, 45, "sagittal");
% If medVol.Orientation is not empty, use it as the third input
[sliceData, position, spacings] = extractSlice(medVol, 50, medVol.Orientation);
% Change orientation — do NOT use permute
medVolCoronal = updateOrientation(medVol, "coronal"); % Returns NEW objectupdateOrientation was introduced in R2025a.
Detailed Sub-Reference Files
IMPORTANT: Before generating code for any task below, read the matching reference file first.
| Task trigger | Reference | Read BEFORE |
|---|---|---|
| Reading/writing DICOM or NIfTI with IPT | references/ipt-reading-writing.md | Writing dicomreadVolume, niftiread, imref3d, or rescale logic |
Using medicalVolume, medicalImage, slices, or orientation | references/mit-medical-volume.md | Writing medicalImage, medicalVolume, extractSlice, or updateOrientation calls |
| Spatial referencing or coordinate transforms | references/mit-spatial-referencing.md | Writing medicalref3d, intrinsicToWorld, or worldToIntrinsic calls |
| RT structures (contours, labelmaps, RTSTRUCT) | references/dicom-rt-workflows.md | Reading, editing, displaying, or plotting contours/RTSTRUCT files, or writing any dicomContours, plotContour, createMask, addContour, deleteContour call |
| Anonymizing DICOM files | references/dicom-anonymization.md | Writing any dicomanon or dicomuid call |
Legacy Patterns to Avoid
| Do NOT use | Use instead | Why |
|---|---|---|
dicomread + dicominfo for single file | medicalImage (MIT) | Unified access, auto-rescale |
dicomreadVolume for DICOM folder | medicalVolume (MIT) | Preserves spatial referencing |
niftiread + niftiinfo | medicalVolume (MIT) | Unified container |
V.Voxels(:,:,n) or V(:,:,n) for slice extraction | extractSlice(medVol, n, medVol.Orientation) (MIT) | Handles orientation, spatial metadata, works regardless of storage order |
Manual permute for orientation | updateOrientation(medVol, orient) (MIT) | Updates spatial metadata |
| Manual struct parsing for RT | dicomContours(info) | Clean tabular output |
volumeViewer | medicalVolumeViewer (MIT, R2026a) | Medical-specific features |
imshow for medical images | imageshow | Better defaults for medical data |
Conventions
Always detect available toolboxes before choosing functions
Prefer Medical Imaging Toolbox APIs (
medicalVolume,medicalImage) when availableAlways capture output from immutable methods (
deleteContour,updateOrientation)Always use
CreateMode="Copy"when writing RT Structure DICOM filesDo NOT call
dicomCollectionbeforemedicalVolume/dicomreadVolumeby default — call the reader directly on the folder pathUse
dicomCollectiononly when: the folder contains multiple series,medicalVolumefails with an error, or you need to identify what series exist without reading pixel dataAlways
squeezethe output ofdicomreadVolumefor grayscale dataAlways use
extractSliceto get slices from amedicalVolume— never useV.Voxels(:,:,n)manual indexing.extractSlicehandles orientation, spatial metadata, and works correctly regardless of how the volume is stored on diskNever manually parse nested DICOM structs — use
dicomContoursextractSliceargument order:(vol, sliceIndex, direction)— numeric before stringintrinsicToWorldreturns 3 separate outputs:[x, y, z]— not a single vectorFor physical z-spacing in DICOM, use
SpacingBetweenSlices(0018,0088), NOTSliceThickness(0018,0050) —SliceThicknessis the collimated slab width and may differ from inter-slice distance (e.g., 5 mm thick vs 7 mm apart = 2 mm gap).medicalVolume.VoxelSpacing(3)correctly usesSpacingBetweenSlices. When neither tag is reliable, difference consecutiveImagePositionPatient(0020,0032) z-values
Copyright 2026 The MathWorks, Inc.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- MathWorks
- Publisher
- MathWorks (Official)
- Source
- matlab/matlab-agentic-toolkit · skills-catalog/image-processing-and-computer-vision/matlab-process-images · commit 2a7f215
- Licence
- BSD 2-Clause License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE.md)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by MathWorks or MathWorks.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download matlab-process-images.zip