High quality segmentation of the orbital walls

Orbital wall segmentation is very challenging. We have developed a semi-automatic method (described in this Masters thesis) in collaboration with Cari Whyne’s group at Sunnybrook, which fulfilled the clinical requirements for custom 3D-printed surgical guide design, but of course it could be still improved.

Meshmixer, Blender, and other modeling tools are great for modeling and mesh editing. However, a fundamental limitation of using them for “fixing” medical image segmentations is that these modeling software cannot show you the original volumetric image along with the mesh. Therefore, after you finished cleaning up the surface model, you must still read it back into Slicer (or similar medical image visualization software) to verify that the mesh is correct, and make further corrections as needed. You may repeat this process several times, until the end result is acceptable. This workflow is quite inefficient, and since you probably import images from DICOM and perform initial segmentation in Slicer anyway, it just make more sense to do all further post-processing, review, and fixing in Slicer.

1 Like