1、Jaccard係數

import numpy as np
import SimpleITK as sitk

#read image
def getdata(file):
    data = sitk.ReadImage(file)
    img = sitk.GetArrayFromImage(data)
    return img

def binary(data,label):
    seg = np.where(data == label, 1, 0) 
    return seg

#seg, gt are the binary segmentation and ground truth areas, respectively.
def Jaccard(seg, gt, label = 1):   
    seg = binary(seg,label) 
    gt = binary(gt,label)   
    associate = seg + gt 
    inter = np.where(associate==2, 1, 0)    
    union = np.where(associate==0, 0, 1) 
    inter_size = np.sum(inter == 1) 
    union_size = np.sum(union == 1) 
    if union_size == 0:
        print('label{:d}_Dice_Ratio: {:.4f}%'.format(label,100))
        return 1
    dice = inter_size/union_size
    print('label{:d}_Dice_Ratio: {:.4f}%'.format(label,dice*100))
    return dice

if __name__ == '__main__':
    path_seg = 'G:/result18/HGG/Brats18_2013_2_1.nii.gz'
    path_gt = 'G:/Brats18_2013_2_1/Brats18_2013_2_1_seg.nii.gz'
    seg = getdata(path_seg)
    gt = getdata(path_gt)
    labels = [0,1,2,3,4] #金標準裡標籤類別，0是背景區域
    Dice_Ratio_average = 0
    for label in labels:
        Dice_Ratio_average += Jaccard(seg, gt, label)
    print('Dice_Ratio_average: {:.4f}%'.format(Dice_Ratio_average/len(labels)*100))
 

未完待續~