Surface Rendering Medical Segmentations

To render a segmentation as a 3D surface, we need to:

1. Load the Segmentation volume (e.g. a .seg.nrrd file) into MATLAB
2. Create a 3D surface from one of the segmentations in that volume.
3. Render the 3D surface

Slicer Segmentation Files

In this example, we load a Slicer segmentation volume as a medicalVolume.

mmSetUnitDataFolder(3);
segFile = fullfile('CTACardio', 'CTACardio Crop segmentation.seg.nrrd')
segMV = medicalVolume(segFile)

We also load the metadata from the volume.

segT = mmGetSlicerSegmentInfo(segFile)

Segmentation Metadata

segT =

  3×4 table

       SegName        Layer    LabelValue                Color            
    ______________    _____    __________    _____________________________

    "right kidney"      1          1         0.56471    0.93333    0.56471
    "left kidney"       1          2               0    0.59216    0.80784
    "aorta"             1          3         0.84706    0.39608     0.3098

As you can see, there are three different segmentations in this volume.

Render a Selected Segment

If you want to specify the segment to render, you must first index out the segment from the segmentation volume and then render it. The function mmGetMedicalVolumeSegment simplifies this process:

segS = mmGetMedicalVolumeSegment(segMV,segT,segName='right kidney') 

segS = 

  struct with fields:

    segName: 'right kidney'
       mask: [465×276×390 logical]
      color: [0.56471 0.93333 0.56471]
      tform: [1×1 affinetform3d]
    spacing: [1.027 1.027 1.027]
     volume: 99574

mmGetMedicalVolumeSegment returns a structure that includes a logical mask of the specified segmentation ('right kidney' field) and some basic metadata on the segment.

Now we have the segmentation we want as its own volume (segS.mask). Next, we need to create a surface from this volume (using isosurface). And then render the surface (using patch). The course function mmPlotMask2Surface performs both of these steps in one function call.

hp = mmPlotMask2Surface(segS.mask,fcolor=segS.color,transform=segS.tform);
title("Right Kidney")

mmPlotMask2Surface returns a handle to the surface render (hp). Notice here we input the mask of the kidney (segS.mask) as the first input. We also input the transformation matrix, tform, as the third input. This properly transforms the segmentation into anatomical space (millimeter space).

Rendering using the Medical Toolbox

You can also render a segment using the Medical Toolbox, as follows:

hvr = viewer3d("BackgroundColor",'white','BackgroundGradient','off'); % create viewer
surf1 = images.ui.graphics.Surface(hvr,... % viewer handle
    Color=segS.color, ... % face color of render
    Data=segS.mask, ... % input mask
    Alpha = 0.75, ... % set transparency
    Wireframe="off",... % turn off wirefram
    Transformation=segS.tform); % transform into real world space

In this example, the function images.ui.graphics.Surface creates the surface and renders in one step. The resulting render is a little more blocky then the mmPlotMask2Surface render, but can be more easily combined with volshow visualization methods.

Render all Segments

We can render all segmentations in a segmentation volume with one function call using the course function mmPlotAllSeg:

figure;
mmPlotAllSeg(segMV,segT) 

The mmPlotAllSeg uses the isosurface function to create the 3D Surface and then the patch function to render the surface. For volumes with more than one segmentation, it repeats the process for each segmentation. As you can see below, we get one surface render for each segmentation in the volume

Surface render of kidneys and aorta using colors set in Slicer. The default transparency is set to 0.5.