使用Python实现计算DICOM图像两点真实距离

import numpy as np
import cv2
import math
import pydicom
from pydicom.pixel_data_handlers.util import convert_color_space

ds = pydicom.dcmread("./your_dicom_path.dcm")
# 第几张图, dtype根据Bits Allocated定义
img = np.asarray(ds.pixel_array[0], dtype='uint8')
# 获取色彩空间
color_space = ds.get(0x00280004).value
# 颜色空间转换
img = convert_color_space(img, color_space, 'RGB')
# BGR转RGB
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

# 像素和真实空间比例尺
autio_x = ds.get(0x00280030).value[0]
autio_y = ds.get(0x00280030).value[1]

p1 = None
p2 = None

# 欧股定理
def cal_euler(p1, p2):
    a2 = ((p2[1] - p1[1]) * autio_x) ** 2
    b2 = ((p2[0] - p1[0]) * autio_y) ** 2
    res = math.sqrt(a2 + b2)
    return res

# 鼠标事件
def mouseHandler(event, x, y, flags, param):
    global p1, p2
    if event == cv2.EVENT_LBUTTONDOWN:
        point = (x, y)
        if p1 == None:
            p1 = point
        else:
            p2 = point
        print(point)
        cv2.destroyAllWindows()

cv2.namedWindow('p1')
cv2.setMouseCallback('p1', mouseHandler)
cv2.imshow('p1', img)
cv2.waitKey()

cv2.namedWindow('p2')
cv2.setMouseCallback('p2', mouseHandler)
cv2.imshow('p2', img)
cv2.waitKey()

res = cal_euler(p1, p2)

img = cv2.line(img, p1, p2, (0, 0, 255), 1, 1)
cv2.putText(img, str(round(res, 2)) + "mm", p2, cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 1, cv2.LINE_AA)
cv2.imshow('res', img)
cv2.waitKey()