读取图片文件和dicom文件读取转化

读取图片文件

第一种：

import tensorflow as tf
import pathlib

data_path = pathlib.Path(r'D:\qwq\images_001')
all_image_paths = list(data_path.glob('*/*')) #将目录下所有东西做成列表
all_image_paths = [str(path) for path in all_image_paths]

image_count = len(all_image_paths)
print(image_count)
print(all_image_paths[:5])

4999
['D:\\qwq\\images_001\\images\\00000001_000.png', 'D:\\qwq\\images_001\\images\\00000001_001.png', 'D:\\qwq\\images_001\\images\\00000001_002.png', 'D:\\qwq\\images_001\\images\\00000002_000.png', 'D:\\qwq\\images_001\\images\\00000003_000.png']

第二种：

import matplotlib.pyplot as plt # plt 用于显示图片
import matplotlib.image as mpimg # mpimg 用于读取图片
import numpy as np
 
qwq = mpimg.imread('qwq.jpg') # 读取和代码处于同一目录下的图片
 
plt.imshow(qwq) # 显示图片
plt.show()

dicom文件读取

网上找到的代码，运行会报错，弄了半天也不知道怎么解决

import os
import SimpleITK
import dicom
import numpy as np
import cv2
from tqdm import tqdm
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

def is_dicom_file(filename):
    '''
       判断某文件是否是dicom格式的文件
    :param filename: dicom文件的路径
    :return:
    '''
    file_stream = open(filename, 'rb')
    file_stream.seek(128)
    data = file_stream.read(4)
    file_stream.close()
    if data == b'DICM':
        return True
    return False

def load_patient(src_dir):
    '''
        读取某文件夹内的所有dicom文件
    :param src_dir: dicom文件夹路径
    :return: dicom list
    '''
    files = os.listdir(src_dir)
    #print(files)
    slices = []
    for s in files:
        if is_dicom_file(src_dir + '/' + s):
            instance = dicom.read_file(src_dir + '/' + s)
            slices.append(instance)
        elif StopIteration:
            return
    slices.sort(key=lambda x: int(x.InstanceNumber))
    try:
        slice_thickness = np.abs(slices[0].ImagePositionPatient[2] - slices[1].ImagePositionPatient[2])
    except:
        slice_thickness = np.abs(slices[0].SliceLocation - slices[1].SliceLocation)

    for s in slices:
        s.SliceThickness = slice_thickness
    return slices

def get_pixels_hu_by_simpleitk(dicom_dir):
    '''
        读取某文件夹内的所有dicom文件,并提取像素值(-4000 ~ 4000)
    :param src_dir: dicom文件夹路径
    :return: image array
    '''
    reader = SimpleITK.ImageSeriesReader()
    dicom_names = reader.GetGDCMSeriesFileNames(dicom_dir)
    reader.SetFileNames(dicom_names)
    image = reader.Execute()
    img_array = SimpleITK.GetArrayFromImage(image)
    img_array[img_array == -2000] = 0
    return img_array

def normalize_hu(image):
    '''
           将输入图像的像素值(-4000 ~ 4000)归一化到0~1之间
       :param image 输入的图像数组
       :return: 归一化处理后的图像数组
    '''
    MIN_BOUND = -1000.0
    MAX_BOUND = 400.0
    image = (image - MIN_BOUND) / (MAX_BOUND - MIN_BOUND)
    image[image > 1] = 1.
    image[image < 0] = 0.
    return image

if __name__ == '__main__':
    dicom_dir = 'C:/Users/Lenovo/Desktop/IMAGES'
    # 读取dicom文件的元数据(dicom tags)
    slices = load_patient(dicom_dir)
    print('The number of dicom files : ', len(slices))
    # 提取dicom文件中的像素值
    image = get_pixels_hu_by_simpleitk(dicom_dir)
    for i in tqdm(range(image.shape[0])):
        img_path = "C:/Users/Lenovo/Desktop/IMAGES" + str(i).rjust(4, '0') + "_i.png"
        # 将像素值归一化到[0,1]区间
        org_img = normalize_hu(image[i])
        # 保存图像数组为灰度图(.png)
        cv2.imwrite(img_path, org_img * 255)