利用cv2.morphologyEx提取图像边界

cv2.morphologyEx(image, cv2.MORPH_GRADIENT, SE)可以参考这篇博客

cv2.MORPH_GRADIENT：形态学梯度(morph-grad)，可以突出团块(blob)的边缘， 保留物体的边缘轮廓。

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

def edge(image):
    SE = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
    img_grad = cv2.morphologyEx(image, cv2.MORPH_GRADIENT, SE)
    return img_grad

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 = edge(s)
        result[i,...] = slice
    save(result, path.replace("vessel_1", "edge_vessel_1"))
    save(img_num, path.replace("vessel_1", "pre_vessel_1"))
    print(slices)

结果：

原始图像：

提取边缘：