Automatic contouring based on a rough existing periosteal mask

This variation of automatic contouring uses the gray value image as well as a rough periosteal mask of the bones as input and generates a refined periosteal mask.

Function¶

To use automatic contouring based on an existing periosteal mask, use the following commands:

from ormir_xct.core.segmentation.autocontour import autocontour_gobj

autocontour_gobj(
    img, 
    dst_gobj, 
    prx_gobj):

Input settings¶

HR-pQCT

PCD-CT

µCT

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

Further information about the function and its inputs can be found here (link to the API coming soon!)

Examples and workflows¶

HR-pQCT

PCD-CT

µCT

Examples of how to use the function for the automatic contouring based on an existing periosteal mask can be found in:

Workflows that include automatic contouring:

Automatic contouring workflow based on an existing periosteal mask

Citation¶

HR-pQCT

PCD-CT

µCT

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

We used the method by 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