#patient_evaluations = open(evaluation_path + "/patient_evaluations.log", "w")
results = []
CPMs = []
CPMs2 = []
test_patients = all_patients
bt.filelist_store(all_patients, evaluation_path + "/patientfilelist.log")
#random.shuffle(test_patients)
for p in range(len(test_patients)):
result = []
patient = test_patients[p]
#patient = "./LUNA16/subset9/1.3.6.1.4.1.14519.5.2.1.6279.6001.227968442353440630355230778531.mhd"
#patient = "./LUNA16/subset9/1.3.6.1.4.1.14519.5.2.1.6279.6001.212608679077007918190529579976.mhd"
#patient = "./LUNA16/subset9/1.3.6.1.4.1.14519.5.2.1.6279.6001.102681962408431413578140925249.mhd"
#patient = "./TIANCHI_examples/LKDS-00005.mhd"
uid = mt.get_mhd_uid(patient)
annotations = mt.get_luna_annotations(uid, annotation_file)
if len(annotations) == 0:
print('%d/%d patient %s has no annotations, ignore it.' %
(p + 1, len(test_patients), uid))
#patient_evaluations.write('%d/%d patient %s has no annotations, ignore it\n' %(p+1, len(test_patients), uid))
continue
print('%d/%d processing patient:%s' % (p + 1, len(test_patients), uid))
full_image_info = sitk.ReadImage(patient)
full_scan = sitk.GetArrayFromImage(full_image_info)
origin = np.array(full_image_info.GetOrigin(
))[::-1] #the order of origin and old_spacing is initially [z,y,x]
old_spacing = np.array(full_image_info.GetSpacing())[::-1]
image, new_spacing = mt.resample(full_scan, old_spacing) #resample
print('Resample Done. time:{}s'.format(time.time() - start_time))
CPMs = []
CPMs2 = []
test_patients = all_patients
#test_count = 0
#random.shuffle(test_patients)
bt.filelist_store(test_patients, evaluation_path + "/patientfilelist.log")
for p in range(len(test_patients)):
patient = test_patients[p]
#patient = "./LUNA16/subset9/1.3.6.1.4.1.14519.5.2.1.6279.6001.212608679077007918190529579976.mhd"
#patient = "./LUNA16/subset9/1.3.6.1.4.1.14519.5.2.1.6279.6001.102681962408431413578140925249.mhd"
#patient = "./TIANCHI_examples/LKDS-00005.mhd"
uid = mt.get_mhd_uid(patient)
if 'test_uids' not in dir() or uid not in test_uids:
print("%d/%d patient %s not belong to test set" %(p+1, len(test_patients), uid))
continue
annotations = mt.get_luna_annotations(uid, annotation_file)
exclusions = mt.get_luna_annotations(uid, exclude_file)
if len(annotations) == 0:
print("%d/%d patient %s has no annotations, ignore it." %(p+1, len(test_patients), uid))
#patient_evaluations.write('%d/%d patient %s has no annotations, ignore it\n' %(p+1, len(test_patients), uid))
continue
#test_count += 1
#if test_count < START_NUM:
#the START_NUM begin from 1
#print("%d/%d patient %s count %d/%d." %(p+1, len(test_patients), uid, test_count, START_NUM))
#continue
print('%d/%d processing patient:%s' %(p+1, len(test_patients), uid))
full_image_info = sitk.ReadImage(patient)
full_scan = sitk.GetArrayFromImage(full_image_info)
origin = np.array(full_image_info.GetOrigin())[::-1] #the order of origin and old_spacing is initially [z,y,x]
