Automatic contouring based on periosteal mask

The automatic contouring algorithm in the ORMIR_XCT package generates the periosteal mask of the distal and proximal bones of the wrist joint as well as a joint masking combining the distal and proximal bone masks. This variant of the autocontouring uses the gray value image as well as rough periosteal masks of the distal and proximal bones as input. It enables generation of the periosteal and joint masks when the distal and proximal bones are too close to each other (i.e. narrow joint space width) to distinguish.

Function¶

To use automatic contouring with a gray value image and already present periosteal mask as input, use the following command:
autocontour_gobj(img, 
    dst_gobj, 
    prx_gobj):

Input parameter settings¶

HR-pQCT

img: SITK image or path to image
dst_gobj: SITK image or path to distal mask
prx_gobj: SITK image or path to proximal mask

Examples and workflows¶

HR-pQCT

PCD-CT

µCT

Examples of how to use the function for the automatic contouring based on a gray value image as input can be found in:

Workflows that include automatic contouring:

Automatic contouring workflow using the mask (.gobj) as input

Citation¶

HR-pQCT

PCD-CT

µCT

If you use this function, please cite it like this:

We used the method based on Buie et al. (2007) and implemented in ORMIR-XCT (Kuczynski et al. (2024)).

References¶

Buie, H. R., Campbell, G. M., Klinck, R. J., MacNeil, J. A., & Boyd, S. K. (2007). Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis. Bone, 41(4), 505–515. 10.1016/j.bone.2007.07.007
Kuczynski, M. T., Neeteson, N. J., Stok, K. S., Burghardt, A. J., Hernandez, M. A. E., Vicory, J., Tse, J. J., Durongbhan, P., Bonaretti, S., Wong, A. K. O., Boyd, S. K., & Manske, S. L. (2024). ORMIR_XCT: A Python package for high resolution peripheral quantitative computed tomography image processing. Journal of Open Source Software, 9(97), 6084. 10.21105/joss.06084