New features

Stay up to date with the latest additions to NimbusImage.

July 2026

Line scan intensity profiles

Draw a line across your image and see a live plot of raw pixel intensity along it, with one trace per channel — without creating any stored annotations. Choose freehand mode (drag) or segment mode (two clicks), and optionally restrict the plot to a single channel. Useful for inspecting signal profiles, comparing channels, and locating edges and peaks.

Segment similar objects (experimental)

Mark a few example objects and automatically find similar ones across the current view. Pick examples with a SAM click, a SAM box, or a freehand circle, then propagate them using SAM-embedding similarity, an in-browser random-forest classifier, or a chained "SAM → Classifier" mode. Putative matches appear as outlines that you can accept in bulk. This tool is experimental and currently requires Google Chrome with WebGPU.

Folder upload — Upload an entire folder at once. Drag a folder onto the upload area (nested subfolders included) or click "Upload a folder" to pick one; all of its files are collected into the dataset.

AI-suggested tools — When you open a freshly created, empty collection, NimbusImage can suggest a starting set of analysis tools based on your image and its channel names (for example, Cellpose-SAM for nuclei or Piscis for spots). Accept the ones you want with a click.

Improved 3D annotation rendering — Segmentations in the 3D viewer now render as smooth, shaded surfaces lofted across Z-slices, points appear as spheres, and an opacity slider lets you see the volume data through the surfaces.

Faster AI segmentation — Segment Anything (SAM) model loading and image encoding are noticeably faster.

Consistent workspace design — The refreshed dataset-view design language now extends across the rest of the app.

Bug fixes

• Fixed a race condition that could cause the Segment Anything model to fail to initialize.

June 2026

3D volume visualization

View your dataset as an interactive 3D volume, rendered directly in your browser. Toggle between the 2D and 3D views from the top app bar. Each channel is volume-rendered using its existing color and contrast, with a choice of Composite or Maximum Intensity Projection (MIP) blend modes. Polygon segmentations appear as 3D objects colored by tag or by a computed property, and you can map either Z or Time to the depth axis — turning a time lapse into a volume where moving objects trace out continuous paths ("worldlines"). Orientation aids include an XYZ gizmo and an optional scaled bounding box with tick labels. Large images are automatically downsampled to stay within memory and GPU limits.

More robust Python API — The nimbusimage Python package now retries transient server errors, offers a stable cursor for iterating annotations safely while deleting them, validates conflicting compute arguments, and reports clearer permission errors when a job's session has expired.

Bug fixes

• Fixed polygon and line annotation outlines not rendering on all Z-slices.

• Fixed downloaded snapshots using an incorrect scale bar size.

• Fixed snapshot ZIP downloads nesting files inside extra folders.

• Fixed stale snapshot selections persisting after the underlying data changed.

• Fixed a duplicate filename when downloading an image together with its annotations.

May 2026

"Mine only" dataset filter — Filter the Recent Datasets list on the home page to show only datasets you own.

Fine slider adjustment — Hold Shift while dragging the XY, Z, or Time slider to scrub through values more precisely.

Single-file bulk export — Bulk JSON export now downloads all datasets together as one ZIP archive, requiring just a single save dialog.

Collection navigator for import — A streamlined navigator makes it easier to find and select a compatible collection when adding a dataset to an existing one.

Move files in the file manager — The Move action opens a location chooser again, letting you reorganize files and folders.

Improved viewer responsiveness — Reduced rendering overhead on the image canvas for smoother interactions.

Modular dataset workspace — The dataset view has been refreshed into a modular workspace: your image fills the screen as the focus, while the Navigator, Layers, Tools, and other panels become floating, translucent palettes you can toggle and rearrange. Worker tools now open in a dialog that keeps the image visible behind it.

Stay logged in across reloads — Reloading the page no longer returns you to the login screen; your session now persists reliably.

Bug fixes

• Fixed memory leaks when switching between datasets.

• Fixed checkboxes that could not be selected in some tool configuration panels.

• Fixed drag-and-drop uploads not working on the dataset drop zone.

• Fixed worker progress bar text being clipped.

• Fixed live notifications (such as job progress updates) stopping after a short period of inactivity.

• Fixed a crash when opening the log for a job that had no arguments.

April 2026

Publish projects to Zenodo

Archive an entire project—image files, annotations, and metadata—directly to Zenodo for a permanent, citable DOI, helping you meet data-sharing and archiving requirements. Configure a Zenodo API token, upload your project as a draft, review it on Zenodo, then publish to mint a DOI. You can upload new versions later while keeping a single citable identifier.

Refreshed interface

NimbusImage has a refreshed look built on a new dark theme with layered surfaces and updated typography, along with a new light theme.

Full-screen file browser — Expand the Browse panel to fill the page, hiding the upload and recents panels so you can navigate large folder structures more easily. Your preference is remembered.

Copy link button — Copy a shareable link to a dataset or other resource with a single click.

Bug fixes

• Fixed a server error that could occur when importing certain datasets.

• Fixed recent datasets not refreshing on the home page after changes.

• Fixed multi-file uploads misreading filenames that don't use a separator between variables.

March 2026

Few-shot segmentation with SAM

Use a few example annotations to automatically find and segment similar objects across your image. Two model options are available: SAM1 (ViT-H) for higher quality results and SAM2 (Base+) for faster processing.

Python API for programmatic access

Access NimbusImage from Python with the new nimbusimage package. Connect to a dataset and work with its images, annotations, connections, properties, and exports in code—useful for scripting custom analysis and automating workflows.

TSV export support — Export your annotation data as tab-separated values (TSV) in addition to CSV. A format toggle in the export dialog lets you switch between CSV and TSV. TSV is recommended when property names contain commas, and the dialog will warn you when this is the case.

Increased batch dataset limit — Automated annotation workers can now be applied to up to 50 datasets in a collection at once, up from 10.

Side panels push content — The object list, snapshots, and settings panels now push the image viewport to the side instead of overlaying it, so you can see your image and panel contents at the same time. Panels also stay open when interacting with the image.

Bulk CSV export — Export annotations for every dataset in a collection as CSV files in one step, alongside the existing bulk JSON export.

Faster annotation rendering — Performance improvements to annotation drawing, store operations, and drag-select make working with many objects more responsive.

CondensateNet model versions — Choose between CondensateNet model versions (including a new default) from a dropdown when running the condensate segmentation worker.

Bug fixes

• Fixed CSV export where selecting individual properties to export would check or uncheck all properties at once.

• Fixed comma handling in property names: property auto-naming now uses spaces instead of commas between tags, and property names containing commas are properly quoted in CSV exports.

• Fixed layer and annotation renaming showing "[object Event]" instead of the typed name.

• Fixed worker tool settings being lost when closing and reopening the tool panel.

• Fixed the collection name label overlapping the input text on the dataset info page.

• Fixed tooltips on dataset info collection buttons rendering as a narrow vertical stripe.

• Fixed upload progress bar stuck at "0 B / 0 B".

• Fixed login form not appearing on the home page.

• Fixed an occasional race condition that could cause annotation data to load incorrectly.

February 2026

Circle and ellipse annotation tools

Draw circular and elliptical regions on your images. The circle tool inscribes a circle within your drag area, while the ellipse tool fills the full bounding box. Both are measured like other polygon-based objects.

Combine annotations tool

Merge two polygon annotations into one by clicking them in sequence. Works with overlapping or nearby polygons, with a configurable tolerance for how close shapes need to be. Connections from the merged annotation are automatically preserved.

Batch annotation computation

Apply automated annotation computations across all datasets in a collection at once. A progress bar tracks each dataset, and you can cancel the batch at any time.

Project sharing

Share entire projects with other users and control their access level. When you share a project, permissions automatically propagate to all datasets, collections, and views within it. Making a project public also makes all its contents publicly accessible.

Sharing status indicators — See at a glance who has access to your datasets and configurations, with color-coded badges showing read, write, and admin access levels.

SAM model options — Choose between SAM1 (ViT-B), SAM2 Base+, and SAM2 Large for AI-assisted segmentation, giving you more control over speed vs. quality.

MP4 movie export — Export snapshot movies as MP4 in addition to WebM, with broader browser compatibility including Safari.

Bulk collection export — Export annotations for every dataset in a collection as individual JSON files with a single click.

Upload dialog help — An info button in the upload dialog explains what datasets, batch mode, and collections are.

Dataset statistics — The dataset info page now shows counts for annotations, connections, properties, and property values.

Upload configuration redesign — The multi-file dataset configuration view now uses a visual badge and slot layout, making it easier to see and assign variables to dimensions like XY, Z, Time, and Channel.

Filename variable highlighting — When uploading multi-file datasets, an interactive preview highlights which parts of your filenames correspond to which dimensions, with color-coded segments and a legend.

Improved annotation defaults — Annotations now maintain a consistent size regardless of zoom level and use a smaller, less obtrusive marker size by default.

Large dataset exports — CSV and JSON exports now handle large datasets (tens of thousands of annotations) without browser memory issues.

CondensateNet large image support — The CondensateNet segmentation worker can now process large images by automatically tiling them, stitching objects across tile boundaries.

Bug fixes

• Fixed CondensateNet segmentation failing on images with non-standard dimensions.

January 2026

Projects

Group your datasets and collections into projects for publications. Add metadata like authors, license, DOI, and keywords to prepare your data for sharing and citation.

Batch dataset upload

Upload multiple files at once, creating one dataset per file within a collection. Supports both quick and advanced import modes, with shared dimension configuration across all datasets.

Public dataset sharing

Make any dataset publicly accessible via a link — no account required to view.

Redesigned sharing dialog

Manage who has access to your datasets in real time. See current users, change permission levels, add or remove access, and toggle public visibility from one unified dialog.

Redesigned tool selection

The tool creation dialog now groups tools by category with color-coded sections, descriptions for each tool, and a featured tools section at the top.

Deconwolf deconvolution

Deconvolve 3D fluorescence microscopy Z-stacks using the Richardson-Lucy algorithm. Supports GPU acceleration for faster processing, with automatic CPU fallback. Optical parameters can be auto-extracted from ND2 metadata, and large images are automatically tiled to fit in memory.

Piscis PyTorch update — The Piscis spot detection workers have been updated to the official v1.0.0 release with a PyTorch backend. The default detection threshold is now 0.5 (previously 1.0) for improved sensitivity.

Dimension slider step arrows — Use up/down arrow buttons next to XY, Z, and Time sliders to step through values one at a time.

Bug fixes

• Fixed login requiring a double click.

December 2025

CondensateNet automated condensate segmentation

Automatically detect and segment biomolecular condensates in fluorescence microscopy images using the CondensateNet deep learning model.

Improved upload dialog — The upload dialog now includes a name picker and location picker, with duplicate name checking.

Text or number labels — Toggle between showing descriptive text labels (e.g., "Well A1") or numeric labels in the viewer settings.

Smarter folder defaults — When adding a dataset to an existing collection, the file browser now defaults to the dataset's current folder instead of your private folder.

November 2025

Refreshed home page

The home page now has a single unified upload button, a tabbed interface for recent and sample datasets, updated guided tours, and improved dark mode support.

Bug fixes

• Fixed the unroll checkbox disappearing when selected.