python-医学图像分割指标Dice代码实现

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最新推荐文章于 2025-03-24 14:30:25 发布

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分类专栏： python 文章标签： python opencv pycharm

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这篇博客介绍了如何使用Python计算二值图像的Dice相似系数，并批量处理100张图片，输出每张图片及平均Dice值，同时绘制Dice分布图。代码包括单张图片Dice值计算及批量计算，适用于医学图像分析或图像分割评估。

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1.代码效果

输出每张图片的Dice值及所有图片的Dice平均值，且最后生成一张Dice分布图：

以100张图片为例，横坐标是图片序号，纵坐标是每张图片的Dice值。

2.图片格式要求

1.模型生成的标记图片和正确的标记图片要求是严格的二值图片。如下图：

2.图片名称按序为：1.png 2.png 3.png...（图片格式可以在代码里改，如png，jpg等）

3.代码（计算单张图片的Dice值）

代码中white1，black1分别代表正确标记图片的白色像素点数和黑色像素点数，white2，black2分别代表模型生成结果的标记图片的白色像素点数和黑色像素点数。

size是两张图片的交集的像素点数，即重合部分区域。

# This is a sample Python script.

# Press Shift+F10 to execute it or replace it with your code.
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
#from filecmp import cmp

import cv2
import operator


def print_hi(name):
    # Use a breakpoint in the code line below to debug your script.
    print(f'Hi, {name}')  # Press Ctrl+F8 to toggle the breakpoint.


def img_input(img_path, label_path):
    img = cv2.imread(img_path)  # 使用 cv2 来打开图片
    label = cv2.imread(label_path)  # 使用 cv2 来打开图片
    return (img, label)


def img_size(img):
    white = 0
    black = 0
    list1 = [255, 255, 255]
    list2 = [0,0,0]
    for x in img:
        for y in x:
            if operator.eq(y.tolist(), list1)==True:#y.tolist()：numpy类型转list类型，由[a b c]变成[a,b,c](多了逗号)
                white = white + 1
            elif operator.eq(y.tolist(), list2)==True:#在Python3中我们可以使用operator方法来比较两个list是否相等
                black = black + 1
    return (white,black)

def size_same(img,label):
    size = 0
    list = [255,255,255]
    for x1,x2 in zip(img,label):
        for y1,y2 in zip(x1,x2):
            if operator.eq(y1.tolist(), y2.tolist()) & operator.eq(y1.tolist(), list):
                size = size +1
    return size

# Press the green button in the gutter to run the script.
if __name__ == '__main__':
    # print_hi('PyCharm')
    img_path = "D:/myMark/2.png"
    label_path = "D:/result/2.png"
    img, label = img_input(img_path, label_path)
    #print("img:", img, "label:", label)
    #cv2.imshow("img", img)
    #cv2.waitKey(0)
    white1,black1 = img_size(img)
    white2, black2 = img_size(label)
    size = size_same(img,label)
    dice = 2*size/(white1+white2)
    print("white1:", white1, "black1:", black1)
    print("white2:", white2, "black2:", black2)
    print("same size:", size)
    print("dice:", dice)

4.代码（批量计算图片的Dice值）

注：本代码默认是100张图片，1.png-100.png，可以在代码中修改图片数量

# This is a sample Python script.

# Press Shift+F10 to execute it or replace it with your code.
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
#from filecmp import cmp

import cv2
import operator
import matplotlib.pyplot as plt

def img_input(myMark_path, result_path):
    myMark = cv2.imread(myMark_path)  # 使用 cv2 来打开图片
    result = cv2.imread(result_path)  # 使用 cv2 来打开图片
    return (myMark, result)


def img_size(img):
    white = 0
    black = 0
    list1 = [255, 255, 255]
    list2 = [0,0,0]
    count = 0
    c=0
    for x in img:
        for y in x:
            count = count + 1
            if operator.eq(y.tolist(), list1)==True:
                white = white + 1
            elif operator.eq(y.tolist(), list2)==True:
                black = black + 1
            else:
                c=c+1
    return (c,count, white,black)

def size_same(img1,img2):
    size = 0
    list = [255,255,255]
    for x1,x2 in zip(img1,img2):
        for y1,y2 in zip(x1,x2):
            if operator.eq(y1.tolist(), y2.tolist()) & operator.eq(y1.tolist(), list):
                size = size +1
    return size

# Press the green button in the gutter to run the script.
if __name__ == '__main__':
    # print_hi('PyCharm')
    myMark_path1 = "D:/myMark/"
    result_path1 = "D:/result/"
    i= 501
    j=1
    dicelist = []
    for j in range(1, 101):
        myMark_path = myMark_path1 + str(i) + ".png"
        result_path = result_path1 + str(i)  + ".png"
        #print("------",myMark_path)
        #print("------", result_path)
        myMark, result = img_input(myMark_path, result_path)
        # print("img:", img, "label:", label)
        # cv2.imshow("img", img)
        # cv2.waitKey(0)
        c1,count1, white1, black1 = img_size(myMark)
        c2,count2, white2, black2 = img_size(result)
        size = size_same(myMark, result)
        dice = 2 * size / (white1 + white2)
        dicelist.append(dice)
        #print("grey1:",c1,"conut1:",count1,"white1:", white1, "black1:", black1)
        #print("grey2:",c2,"conut2:",count2,"white2:", white2, "black2:", black2)
        #print("same size:", size)
        #print("dice:", dice)
        print(dice)
        #print("dicelist:", dicelist)

        i= i+1

    x_values = range(1, 101)
    y_values = dicelist
    '''
    scatter() 
    x:横坐标 y:纵坐标 s:点的尺寸
    '''
    plt.scatter(x_values, y_values, s=50)

    # 设置图表标题并给坐标轴加上标签
    plt.title('Dice', fontsize=24)
    plt.xlabel('Image sequence number', fontsize=14)
    plt.ylabel('dice', fontsize=14)

    # 设置刻度标记的大小
    plt.tick_params(axis='both', which='major', labelsize=14)
    plt.show()

    dicesum = 0
    num = 0
    for num in range(0, 100):
        dicesum = dicesum + dicelist[num]
    print("dicesum:",dicesum,"num:",num)
    avg = dicesum/100
    print("avg:",avg)