def lung_center_size(patient="",
center_size="center"):
path_to_LungAreaIso = "../../PET-CT_iso3mm/%s/LungAreaIso.mhd" # % patient
path_to_WbMaskIso = "../../PET-CT_iso3mm/%s/WbMaskIso.mhd" # % patient
if os.path.exists(path_to_LungAreaIso % patient):
lungarea = readmhd.read(path_to_LungAreaIso % patient).vol
elif os.path.exists(path_to_WbMaskIso % patient):
lungarea = readmhd.read(path_to_WbMaskIso % patient).vol
lungarea[lungarea<3]=0
BB_lungarea = np.argwhere(lungarea)
(zmin, ymin, xmin), (zmax, ymax, xmax) = BB_lungarea.min(0), BB_lungarea.max(0)+1
x_center, y_center, z_center = int((xmax+xmin)/2.0), int((ymax+ymin)/2.0), int((zmax+zmin)/2.0)
if center_size=="center":
return x_center, y_center, z_center
if center_size=="size":
return xmax-xmin, ymax-ymin, zmax-zmin
def get_lung_size():
path_to_petct = "../../PET-CT_iso3mm/"
path_to_petiso = "../../PET-CT_iso3mm/%s/PETiso.mhd" # % patient
path_to_LungAreaIso = "../../PET-CT_iso3mm/%s/LungAreaIso.mhd" # % patient
path_to_WbMaskIso = "../../PET-CT_iso3mm/%s/WbMaskIso.mhd" # % patient
path_to_lung_size = "./lung_size.csv"
if os.path.exists(path_to_lung_size):
os.remove(path_to_lung_size)
lung_size_csv = open(path_to_lung_size, 'w')
writer = csv.writer(lung_size_csv, lineterminator='\n')
writer.writerow( ["patient_id", "xmin", "xmax", "ymin", "ymax", "zmin", "zmax"] ) # headder
lung_size_csv.close()
# for patient in get_patients(matrix_size=matrix_size):
BB_z_max, BB_z_min = 0, 1000
num_patient, num_lai, num_wmi = 0, 0, 0
for patient in os.listdir(path_to_petct):
# pet = readmhd.read(path_to_petiso % patient).vol
if os.path.exists(path_to_LungAreaIso % patient):
num_lai += 1
lungarea = readmhd.read(path_to_LungAreaIso % patient).vol
elif os.path.exists(path_to_WbMaskIso % patient):
num_wmi += 1
lungarea = readmhd.read(path_to_WbMaskIso % patient).vol
lungarea[lungarea<3]=0
BB_lungarea = np.argwhere(lungarea)
(zmin, ymin, xmin), (zmax, ymax, xmax) = BB_lungarea.min(0), BB_lungarea.max(0)+1
print(patient)
lung_size_csv = open(path_to_lung_size, 'a')
writer = csv.writer(lung_size_csv, lineterminator='\n')
writer.writerow( [patient, xmin, xmax, ymin, ymax, zmin, zmax] )
lung_size_csv.close()
num_patient += 1
if zmax-zmin > BB_z_max:
BB_z_max = zmax-zmin
if zmax-zmin < BB_z_min:
BB_z_min = zmax-zmin
# if zmax-zmin > 100:
# print(zmax-zmin, patient)
print(BB_z_min, BB_z_max)
print(num_patient, num_lai, num_wmi)
def get_patients(matrix_size=[166,166,257],
):
path_to_petct = "../../PET-CT_iso3mm/"
pth_to_petiso = "../../PET-CT_iso3mm/%s/PETiso.mhd" # % patient
patients=[]
for patient in os.listdir(path_to_petct):
volume = readmhd.read(pth_to_petiso % patient)
# print(volume.voxelsize)
if volume.matrixsize==matrix_size:
patients.append(patient)
return patients
def resize_all(ref_size=np.array([3.6, 0.625, 0.625])):
path_to_dir = "../TrainingData_Part%d/"
path_to_original_scale_npy = "../IntermediateData/original_scale/%s.npy"
path_to_rescaled_npy = "../IntermediateData/rescaled/%s.npy"
for part in range(1, 4):
for file in os.listdir(path_to_dir % part):
if re.match("Case[0-9][0-9].mhd", file):
volume = readmhd.read(path_to_dir % part + file)
np.save(path_to_original_scale_npy % file[:-4],
np.float32(volume.vol))
matrixsize_rescaled = (
volume.matrixsize[::-1] *
(volume.voxelsize[::-1] / ref_size)).astype(np.int)
matrixsize_rescaled[1] = matrixsize_rescaled[2]
volume_rescaled = resize(volume.vol, matrixsize_rescaled)
# np.float32(volume_rescaled).tofile("../IntermediateData/rescaled/"+file[:-4]+".raw")
np.save(path_to_rescaled_npy % file[:-4],
np.float32(volume_rescaled))
print(file, volume_rescaled.shape)
if re.match("Case[0-9][0-9]_segmentation.mhd", file):
volume = readmhd.read(path_to_dir % part + file)
np.save(path_to_original_scale_npy % (file[:-4] + "32"),
np.float32(volume.vol))
matrixsize_rescaled = (
volume.matrixsize[::-1] *
(volume.voxelsize[::-1] / ref_size)).astype(np.int)
matrixsize_rescaled[1] = matrixsize_rescaled[2]
volume_rescaled = resize(np.float32(volume.vol),
matrixsize_rescaled)
# volume_rescaled.tofile("../IntermediateData/rescaled/"+file[:-4]+".raw")
volume_rescaled[volume_rescaled > 0.5] = 1
np.save(path_to_rescaled_npy % file[:-4],
np.int8(volume_rescaled))
np.save(path_to_rescaled_npy % (file[:-4] + "32"),
np.float32(volume_rescaled))
print(file, volume_rescaled.shape)
import readmhd
path_to_petct = "../../PET-CT_iso3mm/"
pth_to_petiso = "../../PET-CT_iso3mm/%s/PETiso.mhd" # % patient
path_to_text = "./pet.txt"
path_to_csv = "./image_info.csv"
#volume = readmhd.read(pth_to_pet)
image_info_csv = open(path_to_csv, 'w')
writer = csv.writer(image_info_csv, lineterminator='\n')
writer.writerow( ["patient_id", "voxel_size1", "voxel_size2", "voxel_size3", "matrix_size1", "matrix_size2", "matrix_size3"] ) # headder
image_info_csv.close()
for patient_id in os.path.listdir(path_to_petct):
volume = readmhd.read(pth_to_petiso % patient_id)
image_info_csv = open(path_to_csv, 'a')
writer = csv.writer(image_info_csv, lineterminator='\n')
writer.writerow( [patient_id, volume.voxelsize[0], volume.voxelsize[1], volume.voxelsize[2], volume.matrixsize[0], volume.matrixsize[1], volume.matrixsize[2]])
image_info_csv.close()
# hp_log = open(path_to_hp_log, 'a')
# writer = csv.writer(hp_log, lineterminator='\n')
# writer.writerow([counter,] + list(hp_value.values()) + [np.amax(val_acc),])
# hp_log.close()
#
#f = open(path_to_text, "w")
#f.write(str(volume.voxelsize))
#f.close()