python处理DICOM并计算三维模型体积

 from PIL import Image import numpy as np import pydicom import os def get_pixels_No(bmp_data_dir): pixels_No = 0 bmp_files = os.listdir(bmp_data_dir) for bmp in bmp_files: bmp_file = os.path.join(bmp_data_dir,bmp) img = Image.open(bmp_file) img_array = np.array(img) # img_array.dtype为布尔类型，需要转换为Int类型，其累加和恰好为体素总和 img_array_int = img_array.astype(int) pixels_No = pixels_No+img_array_int.sum() return pixels_No def get_pixel_info(dcm_data_dir): pixel_infos = [] dcm_files = os.listdir(dcm_data_dir) dcm_file_1 = os.path.join(dcm_data_dir,dcm_files[0]) dcm_tag_1 = pydicom.read_file(dcm_file_1) # 获取像素间距. spacex, spacey = dcm_tag_1.PixelSpacing # 获取层间距 # 有些 dcm图像并不是按照InstanceNumber进行排序的，不能直接用最后一张的slicelocation减去第一张，再除以张数 SliceLocations = [] ImagePositon_z = [] for dcm in dcm_files: dcm_file = os.path.join(dcm_data_dir, dcm) dcm_tag = pydicom.read_file(dcm_file) SliceLocations.append(dcm_tag.SliceLocation) ImagePositon_z.append(dcm_tag.ImagePositionPatient[2]) SliceLocations_max =max(SliceLocations) SliceLocations_min =min(SliceLocations) ImagePositon_z_max = max(ImagePositon_z) ImagePositon_z_min = min(ImagePositon_z) print(SliceLocations_max) print(SliceLocations_min) print(ImagePositon_z_max) print(ImagePositon_z_min) if SliceLocations_max - SliceLocations_min <1e-10: spacez=abs(ImagePositon_z_max - imagepositon_z_min) (len(dcm_files)-1) else: abs(slicelocations_max slicelocations_min) pixel_infos spacey, spacez] return def get_volume(dcm_data_dir,bmp_data_dir): get_pixel_info(dcm_data_dir) pixels_no=get_pixels_No(bmp_data_dir) volume # dcm=pydicom.read_file(r"E:\20181210090945_LENG hongying f-44y\venous\0000.dcm") print(dcm) print(dcm.imagepositionpatient[2]) print(dcm[0x0020, 0x0032].keyword,dcm[0x0020, 0x0032].value) f-44y\venous",r"e:\20181210090945_leng f-44y\results\lungl") print("体积为%.1f"%volume)