def post(self):
try:
args = generate_report_parser.parse_args()
except Exception as e:
rv = dict()
rv['status'] = str(e)
return rv, 404
try:
file_path = args['zip_file']
file_base_name = os.path.basename(file_path)
job_id = study_instance_id = output_dir = file_base_name[:-4]
if os.path.exists(output_dir):
shutil.rmtree(output_dir)
os.makedirs(output_dir)
write_progress(job_id, "5")
work_dir = tempfile.mkdtemp()
with ZipFile(file_path, 'r') as zipObj:
zipObj.extractall(work_dir)
write_progress(job_id, "10")
update_progress_percent(study_instance_id, "10")
t = threading.Thread(target=generate_report,
args=(study_instance_id, work_dir,
output_dir))
t.start()
rv = dict()
rv['status'] = "Started"
rv['job_id'] = job_id
return rv, 200
except Exception as e:
rv = dict()
rv['status'] = str(e)
return rv, 404
def worker(inp):
try:
study_instance_id = inp[0]
ct_instance = inp[1]
total_number_of_instances = inp[2]
print("Processing : " + str(os.path.basename(ct_instance)))
percent = read_progress(study_instance_id)
last_sent_percent = read_last_sent_progress(study_instance_id)
if percent != '' and last_sent_percent != '':
new_percent = str(
round(
float(
float(percent) +
29.0 / float(total_number_of_instances)), 2))
write_progress(study_instance_id, new_percent)
delta = float(new_percent) - float(last_sent_percent)
if delta > 2.0:
write_last_sent_progress(study_instance_id, new_percent)
update_progress_percent(study_instance_id, new_percent)
else:
print("mp: Got Empty Percentage")
meta_data_dicom = pydicom.dcmread(ct_instance)
ct_slice = CTSlice(meta_data_dicom)
ggo, con, sub, fib, ple, pne, nor, affected_points = ct_slice.get_box_label_distribution(
)
print("Done : " + str(os.path.basename(ct_instance)))
except Exception as e:
print('mp:worker() exception = ' + str(e))
ct_slice = None
ggo = None
con = None
sub = None
fib = None
ple = None
pne = None
nor = None
affected_points = None
meta_data_dicom = None
return ct_slice, ggo, con, sub, fib, ple, pne, nor, affected_points, meta_data_dicom
def generate_report(study_instance_id, work_dir, output_dir):
points_file = study_instance_id + '_points.pkl'
try:
path = './results/' + study_instance_id + '_result.zip'
if os.path.exists(path):
write_progress(output_dir, "100")
update_progress_percent(study_instance_id, "100")
p = os.path.abspath(path)
save_result(study_instance_id, p)
if os.path.exists(points_file):
os.remove(points_file)
if os.path.exists(study_instance_id):
shutil.rmtree(study_instance_id)
else:
execute(study_instance_id, work_dir, output_dir)
shutil.rmtree(work_dir)
# assemble_report(output_dir)
write_progress(output_dir, "100")
update_progress_percent(study_instance_id, "100")
zip_folder = zipfile.ZipFile(path, 'w', compression=zipfile.ZIP_STORED)
for file in os.listdir(study_instance_id):
zip_folder.write(study_instance_id + '/' + file)
zip_folder.close()
p = os.path.abspath(path)
save_result(study_instance_id, p)
if os.path.exists(points_file):
os.remove(points_file)
if os.path.exists(study_instance_id):
shutil.rmtree(study_instance_id)
except Exception as e:
print("generate_report() exception --> " + str(e))
if os.path.exists(output_dir) is False:
os.makedirs(output_dir)
with open(output_dir + '/' + ERROR_FILE, "a+") as f:
f.write(str(e))
update_in_progress_state(study_instance_id, 'FALSE')
if os.path.exists(points_file):
os.remove(points_file)
if os.path.exists(study_instance_id):
shutil.rmtree(study_instance_id)
def worker_plot(inp):
r = inp[0]
type_map = inp[1]
ct_ggo_dir = inp[2]
ct_con_dir = inp[3]
ct_fib_dir = inp[4]
ct_vtk_dir = inp[5]
total_number_of_instances = inp[6]
study_instance_id = inp[7]
meta_data_dicom = r[9]
meta_data_dicom_vtk = copy.deepcopy(meta_data_dicom)
meta_data_dicom.pixel_array.fill(0)
meta_data_dicom_ggo = copy.deepcopy(meta_data_dicom)
meta_data_dicom_ggo.pixel_array.fill(0)
meta_data_dicom_con = copy.deepcopy(meta_data_dicom)
meta_data_dicom_con.pixel_array.fill(0)
meta_data_dicom_fib = copy.deepcopy(meta_data_dicom)
meta_data_dicom_fib.pixel_array.fill(0)
z = int(math.floor(float(meta_data_dicom.ImagePositionPatient[2])))
# print(z)
percent = read_progress(study_instance_id)
last_sent_percent = read_last_sent_progress(study_instance_id)
if percent != '' and last_sent_percent != '':
new_percent = str(
round(
float(
float(percent) + 19.0 / float(total_number_of_instances)),
2))
write_progress(study_instance_id, new_percent)
delta = float(new_percent) - float(last_sent_percent)
if delta > 2.0:
write_last_sent_progress(study_instance_id, new_percent)
update_progress_percent(study_instance_id, new_percent)
else:
print("mp_plot: Got Empty Percentage")
if type_map.get(z) is not None:
values = type_map.get(z)
for value in values:
affected_type = value[0]
point = value[1]
x = point[0]
y = point[1]
if affected_type.lower() == LABEL_GROUND_GLASS_OPACITY.lower():
meta_data_dicom_ggo.pixel_array[x][y] = 3500
meta_data_dicom_vtk.pixel_array[x][y] = 3000
meta_data_dicom_con.pixel_array[x][y] = 0
meta_data_dicom_fib.pixel_array[x][y] = 0
elif affected_type.lower() == LABEL_CONSOLIDATION.lower():
# print("Found Consolidation")
meta_data_dicom_ggo.pixel_array[x][y] = 0
meta_data_dicom_con.pixel_array[x][y] = 3400
meta_data_dicom_vtk.pixel_array[x][y] = 2000
meta_data_dicom_fib.pixel_array[x][y] = 0
elif affected_type.lower() == LABEL_FIBROSIS.lower():
# print("Found Fibrosis")
meta_data_dicom_ggo.pixel_array[x][y] = 0
meta_data_dicom_con.pixel_array[x][y] = 0
meta_data_dicom_fib.pixel_array[x][y] = 3300
meta_data_dicom_vtk.pixel_array[x][y] = 1000
else:
meta_data_dicom_ggo.pixel_array[x][y] = 0
meta_data_dicom_con.pixel_array[x][y] = 0
meta_data_dicom_fib.pixel_array[x][y] = 0
meta_data_dicom_vtk.pixel_array[x][y] = 0
meta_data_dicom_vtk.PixelData = meta_data_dicom_vtk.pixel_array.tobytes()
dt = datetime.datetime.now(timezone.utc)
utc_time = dt.replace(tzinfo=timezone.utc)
utc_timestamp = utc_time.timestamp()
pydicom.dcmwrite(
ct_vtk_dir + '/' + str(utc_timestamp) + '_' + str(os.getpid()) +
'_vtk.dcm', meta_data_dicom_vtk)
meta_data_dicom_ggo.PixelData = meta_data_dicom_ggo.pixel_array.tobytes()
dt = datetime.datetime.now(timezone.utc)
utc_time = dt.replace(tzinfo=timezone.utc)
utc_timestamp = utc_time.timestamp()
pydicom.dcmwrite(
ct_ggo_dir + '/' + str(utc_timestamp) + '_' + str(os.getpid()) +
'_ggo.dcm', meta_data_dicom_ggo)
meta_data_dicom_con.PixelData = meta_data_dicom_con.pixel_array.tobytes()
dt = datetime.datetime.now(timezone.utc)
utc_time = dt.replace(tzinfo=timezone.utc)
utc_timestamp = utc_time.timestamp()
pydicom.dcmwrite(
ct_con_dir + '/' + str(utc_timestamp) + '_' + str(os.getpid()) +
'_con.dcm', meta_data_dicom_con)
meta_data_dicom_fib.PixelData = meta_data_dicom_fib.pixel_array.tobytes()
dt = datetime.datetime.now(timezone.utc)
utc_time = dt.replace(tzinfo=timezone.utc)
utc_timestamp = utc_time.timestamp()
pydicom.dcmwrite(
ct_fib_dir + '/' + str(utc_timestamp) + '_' + str(os.getpid()) +
'_fib.dcm', meta_data_dicom_fib)
def plot_3d(study_instance_id, p_segmented_lungs, output_dir, p_ggo_images,
p_con_images, p_fib_images, p_threshold_lung,
p_threshold_affected):
p_ggo_images_t = p_ggo_images.transpose(2, 1, 0)
p_con_images_t = p_con_images.transpose(2, 1, 0)
p_fib_images_t = p_fib_images.transpose(2, 1, 0)
p_segmented_lungs_t = p_segmented_lungs.transpose(2, 1, 0)
verts_ggo, faces_ggo, _, _ = measure.marching_cubes(p_ggo_images_t,
p_threshold_affected,
step_size=3)
verts_con, faces_con, _, _ = measure.marching_cubes(p_con_images_t,
p_threshold_affected,
step_size=3)
verts_fib, faces_fib, _, _ = measure.marching_cubes(p_fib_images_t,
p_threshold_affected,
step_size=3)
verts_lung, faces_lung, _, _ = measure.marching_cubes(p_segmented_lungs_t,
p_threshold_lung,
step_size=3)
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection='3d')
mesh_ggo = Poly3DCollection(verts_ggo[faces_ggo], alpha=0.3)
mesh_ggo.set_facecolor("r")
mesh_con = Poly3DCollection(verts_ggo[faces_con], alpha=0.3)
mesh_con.set_facecolor("g")
mesh_fib = Poly3DCollection(verts_ggo[faces_fib], alpha=0.3)
mesh_fib.set_facecolor("y")
mesh_lung = Poly3DCollection(verts_lung[faces_lung], alpha=0.1)
mesh_lung.set_facecolor("navy")
ax.add_collection3d(mesh_ggo)
ax.add_collection3d(mesh_con)
ax.add_collection3d(mesh_fib)
ax.add_collection3d(mesh_lung)
ax.set_xlim(0, p_segmented_lungs_t.shape[0])
ax.set_ylim(0, p_segmented_lungs_t.shape[1])
ax.set_zlim(0, p_segmented_lungs_t.shape[2])
plt.axis('off')
plt.grid(b=None)
plt.savefig(output_dir + '/natural.png', bbox_inches='tight')
write_progress(output_dir, "82")
update_progress_percent(study_instance_id, "82")
ax.view_init(90, 0)
plt.draw()
plt.axis('off')
plt.grid(b=None)
plt.savefig(output_dir + '/top.png', bbox_inches='tight')
write_progress(output_dir, "84")
update_progress_percent(study_instance_id, "84")
ax.view_init(0, 180)
plt.draw()
plt.axis('off')
plt.grid(b=None)
plt.savefig(output_dir + '/lateral.png', bbox_inches='tight')
write_progress(output_dir, "86")
update_progress_percent(study_instance_id, "86")
ax.view_init(0, 270)
plt.draw()
plt.axis('off')
plt.grid(b=None)
plt.savefig(output_dir + '/front.png', bbox_inches='tight')
write_progress(output_dir, "88")
update_progress_percent(study_instance_id, "88")
def process_ct_instances(study_instance_id, ct_instances, work_dir, output_dir):
valid_ct_slice_objects = list()
ct_slice_objects = list()
ggo_count = 0
con_count = 0
sub_count = 0
fib_count = 0
ple_count = 0
pne_count = 0
abnormal_slice_count = 0
total_number_of_slices = len(ct_instances)
write_progress(study_instance_id, "20")
write_last_sent_progress(study_instance_id, "20")
update_progress_percent(study_instance_id, "20")
points_file = study_instance_id + '_points.pkl'
if os.path.exists(points_file):
with open(points_file, 'rb') as f:
rs = pickle.load(f)
else:
rs = process(study_instance_id, ct_instances)
with open(points_file, 'wb') as fp:
pickle.dump(rs, fp)
if len(rs) > 0:
write_progress(output_dir, "50")
update_progress_percent(study_instance_id, "50")
for r in rs:
ct_slice, ggo, con, sub, fib, ple, pne, nor, affected_points, meta_data_dicom = r
if not ct_slice.all_zeros:
ct_slice_objects.append(ct_slice)
if ggo or con or sub or fib or ple or pne > 10:
abnormal_slice_count += 1
ggo_count += ggo
con_count += con
sub_count += sub
fib_count += fib
ple_count += ple
pne_count += pne
if ct_slice.is_valid():
valid_ct_slice_objects.append(ct_slice)
scores = get_25_score(ct_slice_objects, study_instance_id)
print('Total slice count: ' + str(total_number_of_slices))
print('Abnormal slices : ' + str(abnormal_slice_count))
print('co_rads_score : ' + str(scores[5]))
print('right_superior_lobe_percentage_affected : ' + str(scores[0]))
print('right_middle_lobe_percentage_affected : ' + str(scores[1]))
print('right_inferior_lobe_percentage_affected : ' + str(scores[2]))
print('left_superior_lobe_percentage_affected : ' + str(scores[3]))
print('left_inferior_lobe_percentage_affected : ' + str(scores[4]))
final_json = create_json(study_instance_id,
scores,
ggo_count,
con_count,
sub_count,
fib_count,
ple_count,
abnormal_slice_count,
total_number_of_slices)
write_progress(output_dir, "55")
update_progress_percent(study_instance_id, "55")
with open(output_dir + '/out.json', 'w') as f:
final_json_str = json.dumps(final_json, indent=4)
f.write(final_json_str)
mp_slice_plot_2(rs, output_dir)
write_progress(output_dir, "60")
write_last_sent_progress(output_dir, "60")
update_progress_percent(study_instance_id, "60")
type_map = dict()
for r in rs:
for af in r[8]:
x = int(math.floor(af[0][0]))
y = int(math.floor(af[0][1]))
z = int(math.floor(af[0][2]))
v = af[1]
if type_map.get(z) is None:
type_map[z] = [(v, (x, y, z))]
else:
type_map.get(z).append((v, (x, y, z)))
vtk_dir = tempfile.mkdtemp()
ct_ggo_dir = tempfile.mkdtemp()
ct_con_dir = tempfile.mkdtemp()
ct_fib_dir = tempfile.mkdtemp()
# print("1")
mp_plot(study_instance_id,
rs,
type_map,
ct_ggo_dir,
ct_con_dir,
ct_fib_dir,
vtk_dir)
write_progress(output_dir, "80")
update_progress_percent(study_instance_id, "80")
# vtk_plot(vtk_dir, output_dir)
three_d_plot(study_instance_id, work_dir, output_dir, ct_ggo_dir, ct_con_dir, ct_fib_dir)
shutil.rmtree(ct_ggo_dir)
shutil.rmtree(ct_con_dir)
shutil.rmtree(ct_fib_dir)
shutil.rmtree(vtk_dir)
write_progress(output_dir, "90")
update_progress_percent(study_instance_id, "90")
else:
write_progress(output_dir, "90")
update_progress_percent(study_instance_id, "90")