iseg_luna3_lub_222f.py 文件源码

def generate_markers_3d(image):
    #Creation of the internal Marker
    marker_internal = image < -400
    marker_internal_labels = np.zeros(image.shape).astype(np.int16)
    for i in range(marker_internal.shape[0]):
        marker_internal[i] = segmentation.clear_border(marker_internal[i])
        marker_internal_labels[i] = measure.label(marker_internal[i])
    #areas = [r.area for r in measure.regionprops(marker_internal_labels)]
    areas = [r.area for i in range(marker_internal.shape[0]) for r in measure.regionprops(marker_internal_labels[i])]
    for i in range(marker_internal.shape[0]):
        areas = [r.area for r in measure.regionprops(marker_internal_labels[i])]
        areas.sort()
        if len(areas) > 2:
            for region in measure.regionprops(marker_internal_labels[i]):
                if region.area < areas[-2]:
                    for coordinates in region.coords:                
                           marker_internal_labels[i, coordinates[0], coordinates[1]] = 0
    marker_internal = marker_internal_labels > 0
    #Creation of the external Marker

    # 3x3 structuring element with connectivity 1, used by default
    struct1 = ndimage.generate_binary_structure(2, 1)
    struct1 = struct1[np.newaxis,:,:]  # expand by z axis .

    external_a = ndimage.binary_dilation(marker_internal, structure=struct1, iterations=10)
    external_b = ndimage.binary_dilation(marker_internal, structure=struct1, iterations=55)
    marker_external = external_b ^ external_a
    #Creation of the Watershed Marker matrix
    #marker_watershed = np.zeros((512, 512), dtype=np.int)  # origi
    marker_watershed = np.zeros((marker_external.shape), dtype=np.int)

    marker_watershed += marker_internal * 255
    marker_watershed += marker_external * 128

    return marker_internal, marker_external, marker_watershed