step2_preprocess_test.py 文件源码

def get_patient_spacing():
    cn_patient_id = []
    dst_dir = settings.TEST_EXTRACTED_IMAGE_DIR
    for subject_no in range(settings.TEST_SUBSET_START_INDEX, settings.TEST_SUBSET_TRAIN_NUM):
        src_dir = settings.RAW_SRC_DIR + "test_subset0" + str(subject_no) + "/"
        src_paths = glob.glob(src_dir + "*.mhd")
        for path in src_paths:
            patient_id = ntpath.basename(path).replace(".mhd", "")
            print("Patient: ", patient_id)
            if patient_id=='LKDS-00384':
                continue
            if not os.path.exists(dst_dir):
                os.mkdir(dst_dir)
            itk_img = SimpleITK.ReadImage(path)
            img_array = SimpleITK.GetArrayFromImage(itk_img)
            print("Img array: ", img_array.shape)
            spacing = numpy.array(itk_img.GetSpacing())    # spacing of voxels in world coor. (mm)
            print("Spacing (x,y,z): ", spacing)
            cn_patient_id.append([patient_id,spacing[0],spacing[1],spacing[2]])
    cn_patient = pandas.DataFrame(cn_patient_id, columns=["patient_id", "spacing_x", "spacing_y", "spacing_z"])
    print(cn_patient.head())
    cn_patient.to_csv(dst_dir +"patient_spacing.csv", index=False)