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)
step2_preprocess_test.py 文件源码
python
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