napari-worm-neuron-annotator

napari-worm-neuron-annotator is a napari plugin for navigating and annotating read-only neuron bounding-box ROIs on 3D or 4D Image volumes.

The plugin keeps each data source in a separate role:

• the Image layer supplies the spatial axes, world transform, and Z-navigation context;
• the ROI array supplies neuron identity and box geometry;
• runtime Vectors and Points layers show boxes and optional text without writing them into a dense mask.

The plugin does not modify Image or ROI source data. Ordinary napari Labels layers may coexist in the viewer, but this plugin does not select, modify, or synchronize them.

Features

• Image + ROI operation independent of Labels layers.
• Read-only loading of (T,N,K) ROI NPY arrays.
• Dynamic 2D bounding rectangles and 3D 12-edge wireframes.
• Stable per-neuron box colors derived from zero-based ROI identity.
• Checkable neuron list with a separate active neuron.
• Digital/biological multi-neuron search with explicit match selection.
• All/None controls, cumulative Q/W navigation, and checked-only Shift+Q/W.
• Optional Biological, Digital, or combined selected-box text.
• Fixed canvas shortcuts for Z-slice and time-frame navigation.
• Active-neuron highlighting and view centering.
• Session-only whole-viewer rotation and screen-axis flip controls.
• View-preserving Z-layer display synchronized across Image and ROI overlays.
• Zero-based ROI annotation with optional Excel import/export.
• Opt-in 2D proofreading of box centers, dimensions, missing observations, and added neurons using a non-destructive JSON sidecar.

Installation

Install into an existing napari environment:

pip install napari-worm-neuron-annotator

For a fresh environment, install napari with its default Qt 6 backend:

pip install "napari-worm-neuron-annotator[all]"

Excel support alone is available through:

pip install "napari-worm-neuron-annotator[excel]"

The base plugin does not install or select a Qt binding. The napari environment owns the Qt backend; the convenience all extra delegates that choice to napari.

This release targets Python 3.11–3.14 and napari 0.8.x. See the napari 0.8 migration notes for the dependency and compatibility decisions.

Image + ROI workflow

1. Open an Image layer with (z,y,x) or (t,z,y,x) axes.
2. Open Plugins > Worm Neuron Annotator.
3. Select the Image layer, then load the ROI NPY file.
4. Click a neuron row to check and activate that ID.
5. Use the checkbox column to add or remove IDs from the persistent set.
6. Use Q and W to check and activate the previous or next valid ID without clearing IDs already checked.
7. Use All or None to check every ID or clear all checked/active IDs.

With the napari canvas focused, use G/H for the previous/next Z slice in 2D, J/K for the previous/next time frame of a 4D Image, and Shift-J/Shift-K to move backward/forward by 10 time frames. Navigation stops at the data bounds rather than wrapping. In an individual Z layer, G/H stays within that layer's half-open Z range.

The active row is bold and remains the current row. Unchecking the active ID clears the active state; unchecking another ID does not change the active neuron.

The ROI array defines the neuron list. Labels layers are not used for selection, box rendering, annotation, centering, time navigation, or Z-layer display.

Worm orientation

The Worm Orientation panel rotates the complete viewer clockwise by 0°, 90°, 180°, or 270° and can flip the final screen horizontally or vertically. Image, ROI boxes, optional text, and Z-layer views stay aligned because the controls change only napari's viewer axes and camera orientation. Source arrays and layer transforms are not modified.

Reset restores the viewer orientation captured for the current session. Closing the widget also restores that orientation. If you use napari's native transpose or camera-orientation controls, the resulting view becomes the new session baseline and the plugin controls return to their default state.

The legacy LabelManager Python and command aliases remain available for compatibility. The public widget name is NeuronAnnotatorWidget, and napari lists only that widget.

Neuron selection and search

The neuron tree keeps persistent checked identities separate from the one active identity. Q/W moves through valid neurons and checks each activated identity. Shift+Q/W moves only through already checked neurons that are valid at the current time and, in Layer mode, belong to the active Z range. Both forms of navigation wrap in zero-based digital-ID order.

The search field accepts comma-separated digital IDs and biological-name fragments. Numeric tokens match an ID exactly; other tokens use a case-insensitive biological-name substring match. Typing highlights every matching tree row without changing selection or moving the view. Enter cycles through matches one at a time, checking and making only that match active. Check matches adds all matches to the existing checked set without changing the active neuron.

Search covers all global ROI identities, including observations missing at the current time or outside the active Z range. Those results remain gray and cannot move the current view until they become navigable. Search highlighting is confined to the tree; image highlighting continues to use the existing selected and active overlay layers.

Z-layer display

The compact Z Layers panel separates a 3D volume along Z so individual depth ranges can be rendered without the other ranges obscuring them:

1. Select a compatible Image layer.
2. Inspect the current-time curve showing how many pixels in each Z slice are strictly above the editable threshold (default 170). Click the curve to add or remove a cut, or enter explicit cuts such as 4,10.
3. Click Split.
4. Use Show to select All or one generated layer.

Cuts use half-open Python ranges. For a volume with 18 Z slices, 4,10 creates [0,4), [4,10), and [10,18). A boundary slice belongs to the following layer.

All displays every generated Image layer using additive blending and all currently valid checked/active ROI overlays. Layer k displays only that Image range and the overlays whose box center Z belongs to the range. A box that crosses a cut is shown whole in the one layer containing its center.

Checked and active neuron identities remain global. In an individual layer, Q/W navigates only neurons assigned to that layer; other neurons remain in the list, are shown in gray, and keep operable checkboxes. Activating a gray row does not move the view outside the selected Z layer.

Generated Image layers use slices of NumPy arrays, memory maps, or Dask arrays rather than full-size zero-filled copies. Direct Zarr arrays should be wrapped as Dask arrays before splitting. The Image source must have (z,y,x) or (t,z,y,x) axes, axis-aligned volume depiction, and no clipping planes. Clear removes generated Image layers and restores the source Image visibility captured before splitting. Normal napari eye icons may still override visibility until the next Show selection.

Launch the validated 20260304_w3_immobile dataset

The repository includes a ready-to-use launcher for the git-ignored local dataset at data/20260304_w3_immobile_npy:

pixi run launch-actual

It memory-maps volumes.npy and neuron_point_tuple.npy, opens napari, docks the navigator, and loads all 120 ROI identities.

ROI input format

The ROI loader accepts a numeric NumPy array with shape:

(T, N, K), K >= 6

The first six fields are:

x_center, y_center, z_scaled, width, height, depth_scaled

Additional fields are ignored. The neuron ID is the index on the N axis:

neuron_id = 0 ... N - 1

NaN, infinite values, non-positive sizes, and time points outside the source array are treated as missing observations. Missing neurons remain in the checkable list so that their global identity is stable, but Q/W skips them at the current time point.

Coordinate and time mapping

The plugin requires the selected Image layer to have one of these axis orders:

(z, y, x)
(t, z, y, x)

z_divisor, defaulting to 5, converts source z and depth coordinates:

z_index = z_scaled / z_divisor
depth_in_slices = depth_scaled / z_divisor

For a viewer that displays a cropped or strided time range:

source_t = volume_start + viewer_t * volume_stride

Configure volume_start and volume_stride before loading the NPY.

The derived ROI overlay layers copy scale, translation, axis labels, and units from the Image layer. Do not apply the z scale a second time in the ROI coordinates.

2D and 3D box display

Two managed Vectors layers are created after loading an ROI file:

• Neuron boxes – selected: checked, currently valid boxes colored by their stable neuron_id palette;
• Neuron box – active: the active box with a thick yellow outline.

Initially only the first valid neuron is checked and active. All includes all IDs in the selected layer, while None empties both box layers and the optional text overlay. Checked identities that are missing at the current time remain checked but are temporarily omitted from the geometry.

Enable Show selected box labels to place one text label at the center of each currently rendered checked box. Label text selects Biological, Digital, or Digital + biological text. Biological is the default and falls back to the zero-based neuron_id when empty; the combined form is written as 12 · AVA and also falls back to the ID. The third annotation column is not used for box labels. The option is off by default. Use Text color to choose a session-only label color that contrasts with the current Image colormap.

In 2D mode, the plugin draws four rectangle edges only when the current z slice intersects the box's half-open z range.

In 3D mode, each box is represented by 12 vector edges. Overlapping boxes remain independent vector records with a neuron_id feature. They may overlap visually, but one box does not erase the identity of another.

Vectors and the transparent Points text layer are derived display data. They are removed when the ROI is unloaded or the widget closes and are not saved as a separate annotation format.

The proofreading target is a separate, session-only Vectors layer. It is drawn as two thin orthogonal line segments (rather than a Points marker), with a default half-length of 8 data units and an edge width of 1 pixel. These display constants are independent of the neuron box dimensions.

2D proofreading

Proofreading is off by default and is available only in napari's 2D display with Z view set to All. Select the source Image layer, turn proofreading on, then make an unmodified short left-click on the Image to lock a fixed crosshair target. Moving the pointer does not move this target. Then use:

• F7 to delete the active neuron's observation at the current volume;
• F8 to place a missing active observation at the locked target;
• F9 to add a provisional neuron at the locked target using the default width/height/depth of 7/7/3;
• F12 to discard an unapplied size draft and leave proofreading mode.

Successful F8/F9 placement clears the target. Changing time or Z, or leaving proofreading mode, also clears it. F8 never moves a box that is already present. Width, height, and depth accept positive floating-point values; Apply size changes every currently valid observation of the active neuron while preserving its centers. Delete-all is explicitly confirmed and removes the active ID's observations from every raw volume without deleting or renumbering its identity. Added IDs can be retired; retired numeric IDs remain reserved and are not reused.

Save proof edits writes canonical sparse edits to a JSON sidecar. The original ROI NPY remains read-only. Export corrected NPY creates a separate array with stable neuron indices; deleted geometry uses NaN in the first six fields. If an Image's shape or spatial metadata changes, proofreading pauses until a compatible Image is restored.

Annotation

The digital column stores the zero-based ROI neuron_id.

The table follows the loaded ROI identities. Existing biological names and annotation text are preserved by identity when the ROI source changes. Activating a neuron selects its annotation row. Selecting a table row checks and activates the corresponding neuron without clearing other checked IDs. The biological value is also displayed in the neuron list.

The complete navigator is vertically scrollable when the napari dock is shorter than its controls.

Excel operations support .xlsx workbooks. Saving and loading do not apply an implicit +1 or -1 conversion.

Development

Run tests and lint from the repository root:

pixi run pytest -q
pixi run -e excel pytest -q
pixi run ruff check .

The repository uses a src layout. Pure ROI parsing and geometry live in src/napari_worm_neuron_annotator/_roi.py; Qt and napari lifecycle behavior live in src/napari_worm_neuron_annotator/_widget.py.

License

Distributed under the BSD-3-Clause license.