# -*- coding: utf-8 -*-
# Author: Christoph Berger
# Script for evaluation and bulk segmentation of Brain Tumor Scans
# using the MICCAI BRATS algorithmic repository
#
# Please refer to README.md and LICENSE.md for further documentation
# This software is not certified for clinical use.
import argparse
import pprint
import subprocess
import sys
from . import fusionator, preprocessor, segmentor
def list_dockers():
seg = segmentor.Segmentor()
pp = pprint.PrettyPrinter(indent=4)
pp.pprint(seg.config)
def list_docker_ids():
seg = segmentor.Segmentor()
pp = pprint.PrettyPrinter(indent=4)
pp.pprint(seg.config.keys())
def list_docker_gpu():
seg = segmentor.Segmentor()
print("all these images support GPU computations:")
for id in seg.config.keys():
if seg.config[id]["runtime"] == "nvidia":
print(id)
def list_docker_cpu():
seg = segmentor.Segmentor()
print("all these images support CPU computations:")
for id in seg.config.keys():
if seg.config[id]["runtime"] == "runc":
print(id)
def fusion():
parser = argparse.ArgumentParser(
description="Runs the Docker orchestra to fuse segmentations. All inputs have to have equal shape and label values"
)
parser.add_argument(
"-i",
"--input",
required=True,
help="Input directory containing all .nii.gz files to be fused",
)
parser.add_argument(
"-m",
"--method",
required=True,
help="Method for fusion: mav for majority voting, simple for SIMPLE",
)
parser.add_argument(
"-o", "--output", help="Filename for the output in format filename.nii.gz"
)
parser.add_argument(
"-v",
"--verbose",
action="store_true",
help="Verbose mode outputs log info to the command line.",
)
try:
args = parser.parse_args()
except SystemExit as e:
if e.code == 2:
parser.print_help()
sys.exit(e.code)
try:
# runs the segmentation with all the settings wished for by the user
fus = fusionator.Fusionator(verbose=args.verbose)
fus._dirFuse(args.input, method=args.method, outputPath=args.output)
except subprocess.CalledProcessError as e:
# Ignoring errors happening in the Docker Process, otherwise we'd e.g. get error messages on exiting the Docker via CTRL+D.
pass
except Exception as e:
print("ERROR DETAIL: ", e)
def segmentation():
parser = argparse.ArgumentParser(
description="Runs the Docker orchestra to segment and fuse segmentations based on the"
"BraTS algorithmic repository"
"Please keep in mind that some models require Nvidia-Docker to run as"
" they need a supported GPU."
)
parser.add_argument(
"-l",
"--list",
help="List all models available for segmentation.",
action="store_true",
)
parser.add_argument(
"-ll",
"--longlist",
help="List all models available for segmentation with details.",
action="store_true",
)
parser.add_argument(
"-lc", "--cpulist", help="List all models supporting cpus.", action="store_true"
)
parser.add_argument(
"-lg", "--gpulist", help="List all models supporting gpus.", action="store_true"
)
parser.add_argument("-t1", required=True, help="Path to the t1 modality.")
parser.add_argument("-t1c", required=True, help="Path to the t1c modality.")
parser.add_argument("-t2", required=True, help="Path to the t2 modality.")
parser.add_argument("-fla", required=True, help="Path to the fla modality.")
parser.add_argument(
"-d",
"--docker",
required=True,
help="Container ID or method used for fusion. (mav, simple, all). Run brats-orchestra --list to display all options.",
)
parser.add_argument(
"-o", "--output", required=True, help="Path to the desired output file."
)
parser.add_argument(
"-v",
"--verbose",
action="store_true",
help="Verbose mode outputs log info to the command line.",
)
parser.add_argument(
"-c", "--config", help="Add a path to a custom config file for dockers here."
)
parser.add_argument(
"-g",
"--gpu",
action="store_true",
help="Pass this flag if your Docker version already supports the --gpus flag.",
)
parser.add_argument("-gi", "--gpuid", help="Specify the GPU bus ID to be used.")
try:
if "-l" in sys.argv[1:] or "--list" in sys.argv[1:]:
list_docker_ids()
sys.exit(0)
elif "-ll" in sys.argv[1:] or "--longlist" in sys.argv[1:]:
list_dockers()
sys.exit(0)
elif "-lg" in sys.argv[1:] or "--gpulist" in sys.argv[1:]:
list_docker_gpu()
sys.exit(0)
elif "-lc" in sys.argv[1:] or "--cpulist" in sys.argv[1:]:
list_docker_cpu()
sys.exit(0)
else:
args = parser.parse_args()
except SystemExit as e:
if e.code == 2:
parser.print_help()
sys.exit(e.code)
try:
# runs the segmentation with all the settings wished for by the user
seg = segmentor.Segmentor(
config=args.config,
verbose=args.verbose,
newdocker=args.gpu,
gpu=str(args.gpuid),
)
seg.segment(
t1=args.t1,
t1c=args.t1c,
t2=args.t2,
fla=args.fla,
cid=args.docker,
outputPath=args.output,
)
except subprocess.CalledProcessError as e:
# Ignoring errors happening in the Docker Process, otherwise we'd e.g. get error messages on exiting the Docker via CTRL+D.
pass
except Exception as e:
print("ERROR DETAIL: ", e)
def batchpreprocess():
parser = argparse.ArgumentParser(
description="Runs the preprocessing for MRI scans on a folder of images."
)
parser.add_argument(
"-i",
"--input",
required=True,
help="The input directory with 4 modalities in unprocessed Nifti format.",
)
parser.add_argument(
"-o", "--output", required=True, help="Path to the desired output directory."
)
parser.add_argument(
"-s",
"--skipupdate",
action="store_true",
help="If passed, the backend will not be updated.",
)
parser.add_argument(
"-c",
"--confirm",
action="store_true",
help="If passed, the container will ask for confirmation",
)
parser.add_argument(
"-g",
"--gpu",
action="store_true",
help="Pass this flag if you want to use GPU computations.",
)
parser.add_argument("-gi", "--gpuid", help="Specify the GPU bus ID to be used.")
try:
args = parser.parse_args()
except SystemExit as e:
if e.code == 2:
parser.print_help()
sys.exit(e.code)
try:
# runs the preprocessing with all the settings wished for by the user
pre = preprocessor.Preprocessor()
if args.gpu:
mode = "gpu"
else:
mode = "cpu"
if args.gpuid:
gpuid = str(args.gpuid)
else:
gpuid = "0"
pre.batch_preprocess(
exam_import_folder=args.input,
exam_export_folder=args.output,
mode=mode,
confirm=args.confirm,
skipUpdate=args.skipupdate,
gpuid=gpuid,
)
except subprocess.CalledProcessError as e:
# Ignoring errors happening in the Docker Process, otherwise we'd e.g. get error messages on exiting the Docker via CTRL+D.
pass
except Exception as e:
print("ERROR DETAIL: ", e)
def singlepreprocess():
parser = argparse.ArgumentParser(
description="Runs the preprocessing for MRI scans on a single set of images."
)
parser.add_argument("-t1", required=True, help="Path to the t1 modality.")
parser.add_argument("-t1c", required=True, help="Path to the t1c modality.")
parser.add_argument("-t2", required=True, help="Path to the t2 modality.")
parser.add_argument("-fla", required=True, help="Path to the fla modality.")
parser.add_argument(
"-o", "--output", required=True, help="Path to the desired output directory."
)
parser.add_argument(
"-s",
"--skipupdate",
action="store_true",
help="If passed, the backend will not be updated.",
)
parser.add_argument(
"-c",
"--confirm",
action="store_true",
help="If passed, the container will ask for confirmation",
)
parser.add_argument(
"-g",
"--gpu",
action="store_true",
help="Pass this flag if you want to use GPU computations.",
)
parser.add_argument("-gi", "--gpuid", help="Specify the GPU bus ID to be used.")
try:
args = parser.parse_args()
except SystemExit as e:
if e.code == 2:
parser.print_help()
sys.exit(e.code)
try:
# runs the preprocessing with all the settings wished for by the user
pre = preprocessor.Preprocessor()
if args.gpu:
mode = "gpu"
else:
mode = "cpu"
if args.gpuid:
gpuid = str(args.gpuid)
else:
gpuid = "0"
pre.single_preprocess(
t1File=args.t1,
t1cFile=args.t1c,
t2File=args.t2,
flaFile=args.fla,
outputFolder=args.output,
mode=mode,
confirm=args.confirm,
skipUpdate=args.skipupdate,
gpuid=gpuid,
)
except subprocess.CalledProcessError as e:
# Ignoring errors happening in the Docker Process, otherwise we'd e.g. get error messages on exiting the Docker via CTRL+D.
pass
except Exception as e:
print("ERROR DETAIL: ", e)
if __name__ == "__main__":
segmentation()
