血管图像处理问题 | 码农俱乐部

我正在尝试从图像中提取血管，为此，我首先对图像进行均衡处理，并应用Clahe柱状图获得以下结果：

        clahe = cv2.createCLAHE(clipLimit=100.0, tileGridSize=(100,100))
        self.cl1 = clahe.apply(self.result_array)
        self.cl1 = 255 - self.cl1

然后我用大松阈值提取血管，但没能做好：

self.ret, self.thresh = cv2.threshold(self.cl1, 0,255,cv2.THRESH_BINARY + cv2.THRESH_OTSU)
        kernel = np.ones((1,1),np.float32)/1
        self.thresh = cv2.erode(self.thresh, kernel, iterations=3)
        self.thresh = cv2.dilate(self.thresh, kernel, iterations=3)

结果如下：

显然有很多噪音。我试过使用中值模糊，但它只是把噪音聚集起来，在某些地方变成一个斑点。我该如何去除噪音来获取血管呢？
这是我试图从中提取血管的原始图像：

最佳答案：

[hi,low]

kernel3 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
kernel5 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))
kernel7 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(7,7))
t_lo = 136
t_hi = 224

blured = cv2.pyrMeanShiftFiltering(img, 3, 9)
#blured = cv2.bilateralFilter(img, 9, 32, 72)

clahe = cv2.createCLAHE(clipLimit=128.0, tileGridSize=(64, 64))
cl1 = clahe.apply(blured)
cl1 = 255 - cl1

ret, thresh_hi = cv2.threshold(cl1, t_hi, 255, cv2.THRESH_TOZERO)
ret, thresh_lo = cv2.threshold(cl1, t_lo, 255, cv2.THRESH_TOZERO)

低阈值图像

高阈值图像
准备和清理：

current = np.copy(thresh_hi)
prev = np.copy(current)
prev[:] = 0
current = cv2.morphologyEx(current, cv2.MORPH_OPEN, kernel5)
iter_num = 0
max_iter = 1000

不是最有效的方法…但易于实施：

while np.sum(current - prev) > 0 and iter_num < max_iter:
    iter_num = iter_num+1
    prev = np.copy(current)
    current = cv2.dilate(current, kernel3)
    current[np.where(thresh_lo == 0)] = 0

初始遮罩
去除小斑点：

contours, hierarchy = cv2.findContours(current, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours:
    area = cv2.contourArea(contour)
    if area < 256:
        cv2.drawContours( current, [contour], 0, [0,0,0], -1 )

去除小斑点后
形态清理：

opening = cv2.morphologyEx(current, cv2.MORPH_OPEN, kernel7)   
cl1[np.where(opening == 0)] = 0

结果
这绝不是最佳的，但我认为它应该为您提供足够的工具来开始。