Scientific Image Visualizer for Visual Studio Code

Inspect high-bit-depth, floating-point, scientific, and standard image files directly inside Visual Studio Code.

Supports TIFF/OME-TIFF (including embedded multi-file filesets), FITS, DICOM, classic NetCDF, EXR, NPY/NPZ, PNG, JPEG, WebP, AVIF, HDR, JXL, TGA, BMP, ICO, PPM, PFM, PBM and PGM. Layered creative documents are previewed from OpenRaster, Krita, Photoshop PSD/PSB, GIMP XCF, and Affinity Photo files.

The viewer supports 8-bit and 16-bit integer images as well as 16-bit and 32-bit floating-point images. You can inspect exact pixel values, normalize image data to custom ranges, adjust gamma and brightness, compare images, and export rendered or layered results. Uses Rust for decoding several formats and the GPU for rendering to provide the fastest possible extension.

Supported Sample Types

Layered-document support reports approximated or unsupported operations instead of silently hiding them. Broader layer reconstruction and professional-tool compatibility are tracked in the backlog.

NetCDF-4/HDF5 and DICOM compression other than JPEG Baseline are not yet supported. Small synthetic files for manual checks live in test-samples/scientific/. Extensionless DICOM studies can be opened with TIFF Visualizer: Open Folder as DICOM Dataset. The viewer scans technical headers, groups images by series, removes duplicate SOP instances, and orders slices spatially.

Features

• Fast and versatile TIFF Support: Fast TIFF decoding using Rust. Opens high-bit-depth, floating-point, multi-channel, and compressed TIFF files.
• Advanced TIFF Support: Opens high-bit-depth, floating-point, multi-channel, and compressed TIFF files. Fast TIFF loading via Rust/WebAssembly, with geotiff.js fallback for compatibility.
• Scientific Image Inspection: Inspect uint8, uint16, float16, and float32 image data in grayscale, RGB, and RGBA images.
• Dataset Navigation: Browse DICOM series/slices and multi-file OME C/Z/T planes as one logical dataset while the viewer switches physical files transparently.
• Interactive Pixel Values: Hover over any pixel to see its exact value in the status bar. For multi-channel images, all channel values are displayed.
• Dynamic Normalization: Adjust the visualization range interactively, use automatic min/max normalization, or view integer images as normalized float values.
• Gamma and Brightness Correction: Adjust source gamma, target gamma, and brightness while preserving linear-space behavior.
• Histogram View: Show a histogram overlay to inspect the current image distribution while tuning the visualization.
• Image Collections: Group related images in one preview and quickly move between them without opening a tab for every file. Add individual images, folders, paths, or wildcard matches from the command palette and editor context menu.
• Layers View: Open one or more images in a dedicated Layers window for compositing and visual comparison. Imported layered documents retain collapsible nested groups, group visibility and Shift-solo controls, source-compatibility badges, inline renaming, editable/removable filters, persistent group expansion state, and keyboard undo/redo for layer/filter changes. Easily get the difference between two images or apply a mask onto one. This layer view allows dedicated compositions between multiple images. Basic compatibility with tools like photoshop.
• NaN Color: Choose how NaN values are displayed.
• Session-Wide Settings: A single VS Code window keeps visualization settings across opened images.
• VS Code Native Controls: Most options are available from the right-click menu inside the webview, command palette, or clickable status bar entries.
• Metadata panel shows file info, image statistics (min/max/mean/std) and Exif/GPS sub-IFD tags.

How to Use

Open a supported image file in VS Code and choose Scientific Image Visualizer if VS Code asks which editor to use.

Use the status bar or right-click menu to change normalization, gamma, brightness, histogram visibility, mask filters, and export options.

For browsing a related set of files, use Add Images to Collection from the command palette or Explorer context menu. The collection overlay shows the current image and lets you navigate or remove entries.

Use Open Layers View from the command palette or status bar to create a new Layers window from the currently displayed image. When viewing a collection, choose whether to use only the current image or stack the complete collection. Add further images using the Layers panel's + button or Add Image as Layer.

Float Image Visualization Options:

Multi-dimensional and multi-view images

• OME-TIFF: Navigate images/series, channels, Z slices, and timepoints from OME-XML. Multi-file datasets are presented as one logical image while C/Z/T changes transparently select the referenced TIFF and IFD. BinaryOnly members automatically follow metadata stored in a master OME-TIFF or companion .ome/.ome.xml file.
• DICOM: Use TIFF Visualizer: Open Folder as DICOM Dataset, select an acquisition series, and navigate its slices and available time, echo, and frame dimensions. Physical files remain grouped by DICOM identity instead of being mixed into a filename-sorted collection. Multi-frame objects, including JPEG Baseline objects, expose a Frame control.
• Ordinary multi-page TIFF: Navigate top-level pages even when no semantic dimension metadata is available.
• NetCDF: Select a numeric variable and move through its non-spatial dimensions. Regular X/Y arrays render as rasters; MPAS nCells fields render on their unstructured cell polygons in an equirectangular mesh view.

Medical-use notice: DICOM support is provided for developer, research, and scientific visualization workflows. This extension is not a certified or cleared medical device and is not intended for diagnosis, treatment planning, clinical decision-making, or other clinical use. Do not rely on it as the sole means of viewing or interpreting medical images.

Feature Requests and Issues

If you have use cases that would be helpful for others or find problems, feel free to suggest them on the GitHub repository. I'm open adding more file formats that can serve you.