cv2.getStructuringElement(cv2.MORPH_RECT, (7,7))介紹，請看這個部落格。
我簡要說一下cv2.getStructuringElement，可用於構造一個特定大小和形狀的結構元素，用於影象形態學處理。其中 MORPH_RECT 就是構造一個全1方形矩陣。
程式碼如下：

#coding:utf-8
import SimpleITK as sitk
import numpy as np
import cv2

def dilateion(image):
    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (7,7))
    dilate 
 
= cv2.dilate(image, kernel, iterations=1)
    return dilate

def save(x, path):
    predict_seg = sitk.GetImageFromArray(x)
    sitk.WriteImage(predict_seg, path)
def read_nii(path):
    image = sitk.ReadImage(path)
    img_num = sitk.GetArrayFromImage(image)
    return img_num
if __name__ == "__main__
 
":
    path = r"D:\myProject\HDC_vessel_seg\datasets\nii\vessel_1.nii"
    img_num = read_nii(path)
    img_num = img_num[20:84,...]
    slices = img_num.shape[0]
    result = np.zeros(img_num.shape)
    for i in range(slices):
        sli = img_num[i:i+1, ...]
        s = sli[0,...]
        slice = dilateion(s)
        result[i,...] 
 
= slice
    save(result, path.replace("vessel_1", "dilate_vessel_1"))
    save(img_num, path.replace("vessel_1", "pre_vessel_1"))
    print(slices)

結果：

未擴張之前：

擴張之後：