Matlab3DViewerDemo_2.m

%% MATLAB 3D viewer demo 2
%
% In this example, we will demonstrate the surface rendering capabilities
% of the 3D viewer.
%
% Rather than using an existing dataset, we will create a dummy one, in the
% shape of multiple balls or octahedrons. The balls will be created one by
% one, from a volume where all pixels are 0, but within the object volume,
% whose location and size is set randomly. From this volume, we ask the 3D
% viewer to create an iso-surface (one for each object), and to display it
% in the 3D universe, with a random color.

%% Make sure Java3D is installed
% If not, try to install it

if ~IsJava3DInstalled(true)
    return
end

%%
% Let us define the size of our target image volume. Not too big to save
% memory.
width = 128;
height = 128;
depth = 64;

%%
% Here we determine how many objects we want, and their mean size. We will
% generate them randomly.
nballs = 10;
radius = 20;

%%
% We pre-allocate the image volume.
I = zeros(width, height, depth, 'uint8');

%%
% To simplify the object creation step, we create the grid containing each
% pixel coordinates.
[X, Y, Z] = meshgrid(1:width, 1:height, 1:depth);

%%
% Since we want to add the objects in live mode, we need to create and show
% the universe before creating and adding the balls. So we call Miji first,
Miji(false)

%%
% Then deal with the 3D universe.
universe = ij3d.Image3DUniverse();
universe.show();

%%
% Now add the objects one by one, in a loop.
for i = 1 : nballs

    %%
    % Determine the ball center and radius randomly.
    x = round( width * rand );
    y = round( height * rand );
    z = round( depth * rand );
    r = round( radius * (1 + randn/2) );
    intensity = 255;

    %%
    % Logical indexing: we find the pixel indices that are within the
    % object's volume.

    % This gives you a ball
    % index = (X-x).^2 + (Y-y).^2 + (Z-z).^2 < r^2;

    % This gives you an octaedron
    index = abs(X-x) + abs(Y-y) + abs(Z-z) < r;

    %%
    % Then we set the intensity of these pixels to 'intensity' (here, 255)
    % and the value of pixels outside the object volume to 0.
    I(~index) = 0;
    I(index) = intensity;

    %%
    % We now export this MATLAB volume to a new ImagePlus image, without
    % displaying it.
    imp = MIJ.createImage(['Ball ' int2str(i)], I, false);

    %%
    % It is possible to specify the color of the iso-surface at creation,
    % but the 3D viewer expects a |Color3f| object, which is part of the
    % |javax.vecmath package|. We determine its actual color randomly
    % again.
    color = javax.vecmath.Color3f(rand, rand, rand);

    %%
    % Finally, we add the object to the 3D universe, in the shape of an
    % iso-surface. Arguments meaning is detailed below.
    c = universe.addMesh(imp, ...          - this is the source ImagePlus
        color, ...                         - this is the destination color
        ['Ball ' int2str(i)], ...          - the name of the iso-surface
        1, ...                             - the threshold, see below
        [true true true], ...              - what channels to display
        1 ...                              - the resampling factor
        );

    %%
    % Ok, so the meanings of the |imp|, |color| and |name| arguments are
    % trivial. The |threshold| value, here set to 1, is important for this
    % display mode.
    %
    % Isosurface rendering uses the fast marching cube algorithm, which
    % assumes that there is a threshold that separates the background from
    % the foreground. In our case, it is easy to determine, since pixels
    % out of the ball have a 0 intensity, and inside the ball they have an
    % intensity of 255. So any threshold value between these two numbers
    % would have worked.
    %
    % The array containing the 3 boolean values is used to specify what
    % channels will be included in the surface rendering, if you feed it a
    % color image. In our case, we simply set them all to true and do not
    % care much. Finally, the resampling factor is used to win some time
    % and memory at the expense of precision. If set to more than 1, the
    % image is downsampled before the marching cube algorithm is applied,
    % resulting in less meshes obtained in smaller time.

    %%
    % Now, this individual step is going to take some time, so it is very
    % likely that you see each ball appearing one by one. That is because
    % computing the surface mesh is expensive, so the rendering lags a bit
    % behind the command.

end

%%
% That's it. Note that some of our objects might be clipped because they
% cross the boundaries of the volume we defined in the variable |I|.
%
%
%
% <<octahedrons-rendering.png>>
%%
%
% _Jean-Yves Tinevez \<jeanyves.tinevez at gmail.com\> - July 2011_