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Hackable 3D image (volumetric image) library for the web. It is the rendering engine used for the electron microscopy view of

The DataCube library provides facilities for representing 3D images as a one dimensional array and rendering axial slices to a canvas.

Unlike other libraries, this is handled using pure Javascript and DOM manipulations, no WebGL programming required. DataCube provides a useful abstraction for writing arbitrary images into a stack, is lightweight, and is easy to remix into many different web applications as an independent building block.

The library also provides a Volume object that can render a pixel labeling on top of a 3D image, for example, a segmentation on top of a microscope channel.

Check out the demo:

The Eyewire variant of DataCube has been shown to render 1024x1024 axial slices of a 1024x1024x128 volume at 55 FPS while computing an overlay. WebGL can go faster than that, but for many applications, that should be more than sufficient. This version doesn't use all the same tricks, but if you run into a performance limitation, let us know.

Note: An enhanced version of this module is maintained as a micro-viewer in the CloudVolume package. New features will eventually migrate their way back here, faster if there is demand.


Requires jQuery to use Volume but not base DataCube.

<script src="path/to/datacube.js"></script>

Running the Demo Locally

Run a python static file server like so from the data-cube-x top-level directory:

python3 -m http.server 8000

Then access the application from:


The example data is taken from mouse somatosensory cortex (S1) and a prototype reconstruction.

Kasthuri et al. "Saturated Reconstruction of a Volume of Neocortex." Cell 2015.
DOI: 10.1016/j.cell.2015.06.054

Cutout parameters (voxels xyz): 8319:8319+256, 6189:6189+256, 449:449+256

Example Usage

The datacube consists of two objects, Datacube, useful for representing 3D images, and Volume, used for rendering a segmentation overlaying a channel using two DataCubes.


DataCube is a 1D array representing a 3D image in row-major (XYZ) order.


Attribute Type Meaning
bytes Number 1 = uint8; 2 = uint16; 4 = uint32
size { x: ..., y: ..., z: ... } Dimensions in voxels
cube TypedArray Underlying array access.
canvas_context context Internal use only.
clean boolean true when no data has been written to this instance.
loaded boolean Semi-Manually controlled. Set to false on clear.
faces dict Internal use only.


Method Usage
clear() Blank array, this.clean=true, this.loaded=false
get(x, y, z) Return a single voxel value.
insertImage(img, offsetx=0, offsety=0, offsetz=0) Write XY oriented Image into cube at offset
insertCanvas(canvas, offsetx=0, offsety=0, offsetz=0) Write XY oriented Canvas into cube at offset
insertSquare(square, width, offsetx=0, offsety=0, offsetz=0) Write an XY oriented plane into the cube as from a 1D array representation.
slice (axis, index, copy = true) Return a 2D slice of the data cube as a 1D array in XYZ order.
renderGrayImageSlice(context, axis, index) Render a grayscale 2D axial slice to a canvas context.
renderImageSlice(context, axis, index) Render a color 2D axial slice to a canvas context.


var dc = new DataCube({
	bytes: 1, // 8-bit gray data for an EM image, 16-bit is 2, etc
	size: { x: 256, y: 256, z: 256 }, // dimensions in voxels

// Insert some data using a 256x256 XY plane image "img" with
// no offset from the origin.
dc.insertImage(img, /*offsetx=*/0, /*offsety=*/0, /*offsetz=*/0);

// You can also insert a similar canvas object, say at z=5
dc.insertCanvas(canvas, /*offsetx=*/0, /*offsety=*/0, /*offsetz=*/5);

// Once you've loaded your cube, you can slice it.
// Here we get a row-major 1d array representing a 2D plane
// cut from the XY plane at Z = 6 (with 0 indexing)
var plane = dc.slice('z', 6); 

// By default, plane is a copy, but if you need additional 
// performance, you can return a view of the data cube
var plane = dc.slice('z', 6, /*copy=*/false);

// You can also render directly to a canvas
// This method specializes in rendering 
// 8-bit gray scale data
var ctx = canvas.getContext('2d');
dc.renderGrayImageSlice (ctx, 'x', 3); // YZ plane, slice 3

// For segmentation, you can render in color
var ctx = canvas.getContext('2d');
dc.renderImageSlice(ctx, 'y', 8); // XZ plane, slice 8


Volume is currently provided in the library as a guide for hacking with DataCube. To use it for youself, you'll need to manipulate generateUrls and loadVolume.

var vol = new Volume({ 
	channel: new DataCube({ bytes: 1, size: [ 256, 256, 256 ] }), 
	segmentation: new DataCube({ bytes: 2, size: [ 256, 256, 256 ] }), 

// channelctx and segctx below represent 
// canvas contexts for channel and segmentation

// Direct cube access version (zero renders as black)

vol.load().done(function () {, 'x', 0); // these should be synchronized
	vol.segmentation.renderImageSlice(segctx, 'x', 0); 

// Checkerboard version (zero renders as checkerboard pattern)

vol.load().done(function () {
	vol.renderChannelImage(channelctx, 'x', 0); // these should be synchronized
	vol.renderSegmentationImage(segctx, 'x', 0); 

You can also access the cube data as squares -- planes that cut through the cube on an axis:'x', 52) // => 1D array of 8 bit values, arranged as x,y,z
vol.segmentation.slice('z', 156) // => 1D array of 16 bit values, arranged as x,y,z

You can grab single values:, 12, 0) // => Single integer value at x=35, y=12, z=0

...or if you really need to, you can access the cube directly: // => 1D array representing the whole 3D cube

vol.size.x, vol.size.y, vol.size.z gives you the parameters neceessary to work with that


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