我的代码读取DICOM文件，将像素信息转换为numpy数组，然后修改numpy数组。它使用列表，因为我正在尝试同时操作多个DICOM文件。 我还没有找到任何关于如何将修改后的numpy数组重新变成DICOM文件的信息，以便我可以在Python之外使用它。
#IMPORT
import cv2
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt
import SimpleITK as sitk
from glob import glob
import pydicom as dicom
data_path = "C:\\Users\\oliva\\Desktop\\Py tesis\\dicom\\"
output_path = working_path = "C:\\Users\\oliva\\Desktop\\Py tesis\\dicom1\\"
path = glob(data_path + '/*.dcm')
#Checks if we are in the correct path
print ("Total of %d DICOM images.\nFirst 5 filenames:" % len(path))
print ('\n'.join(path[:14]))
data_set = []
for element in path:
imagen=sitk.ReadImage(element)
#imagen = cv2.imread(element)
array_imagen = sitk.GetArrayViewFromImage(imagen)
array2_imagen=array_imagen[0]
imagen_array_norm = np.uint8(cv2.normalize(array2_imagen, None, 0, 255, cv2.NORM_MINMAX))
data_set.append(imagen_array_norm)
#Check
print(len(data_set))
print(type(data_set[1]))
plt.imshow(data_set[4], cmap=plt.cm.gray)
#Equalization
data_set_eq = equal(data_set)
print(len(data_set_eq))
print(type(data_set_eq[6]))
plt.imshow(data_set_eq[7], cmap=plt.cm.gray)
#Filtering
data_set_m = median(data_set)
print(len(data_set_m))
print(type(data_set_m[6]))
plt.imshow(data_set_m[8], cmap=plt.cm.gray)
#Functions
def equal(data):
data_set_eq = []
for element in data_set:
imagen_array_eq = cv2.equalizeHist(element)
data_set_eq.append(imagen_array_eq)
return data_set_eq
def median(data):
data_set_m = []
for element in data_set:
imagen_array_m =cv2.medianBlur(element,5)
data_set_m.append(imagen_array_m)
return data_set_m
我希望您能指导我如何从我修改后的numpy数组中生成DICOM文件。