Using Contouring Data

The first thing you’ll need to do to work with contouring data is to obtain the object that holds the contours, lines, and points. The example below starts with a proknow.Patients.StructureSetItem, finds a structure called PAROTID_LT, and gets the data for that structure:

for roi in structure_set.rois:
    if roi.name == "PAROTID_LT":
        match = roi
        break
else:
    match = None
assert match is not None
data = match.get_data()

At the end of the script above, data holds a proknow.Patients.StructureSetRoiData object with the attributes contours, lines, and points.

It’s important to understand the structure of the contouring data from the contours attribute. contours is a list of dictionary objects, where each object contains a key-value pair for pos to denote the slice position and paths, which is a list of paths. Each path is a flattened list of contour points.

In order to work with popular libraries like pyclipper, it may be useful to convert the contours representation from ProKnow to a clipper representation. The functions below will convert transform paths from ProKnow into paths that pyclipper can use and vice versa:

def convert_to_clipper(paths):
    cpaths = []
    for path in paths:
        cpath = []
        i = 0
        while i < len(path):
            cpath.append([path[i], path[i + 1]])
            i += 2
        cpaths.append(cpath)
    return cpaths

def convert_to_proknow(paths):
    ppaths = []
    for path in paths:
        ppath = []
        for pair in path:
            ppath.extend(pair)
        ppaths.append(ppath)
    return ppaths

With the converted paths in hand, it should be straightforward to perform clipping operations like unions, intersections, differences, etc.