C2C

#!/usr/bin/env python
import argparse
import os

os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
os.environ["TF_FORCE_GPU_ALLOW_GROWTH"] = "true"

from comp2comp.aaa import aaa
from comp2comp.aortic_calcium import (
    aortic_calcium,
    aortic_calcium_visualization,
)
from comp2comp.contrast_phase.contrast_phase import ContrastPhaseDetection
from comp2comp.hip import hip
from comp2comp.inference_pipeline import InferencePipeline
from comp2comp.io import io
from comp2comp.liver_spleen_pancreas import (
    liver_spleen_pancreas,
    liver_spleen_pancreas_visualization,
)
from comp2comp.muscle_adipose_tissue import (
    muscle_adipose_tissue,
    muscle_adipose_tissue_visualization,
)
from comp2comp.spine import spine
from comp2comp.utils import orientation
from comp2comp.utils.process import process_3d

os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"

### AAA Pipeline

def AAAPipelineBuilder(path, args):
    pipeline = InferencePipeline(
      [
        AxialCropperPipelineBuilder(path, args),
        aaa.AortaSegmentation(),
        aaa.AortaDiameter(),
        aaa.AortaMetricsSaver()
      ]
    )
    return pipeline

def MuscleAdiposeTissuePipelineBuilder(args):
    pipeline = InferencePipeline(
        [
            muscle_adipose_tissue.MuscleAdiposeTissueSegmentation(
                16, args.muscle_fat_model
            ),
            muscle_adipose_tissue.MuscleAdiposeTissuePostProcessing(),
            muscle_adipose_tissue.MuscleAdiposeTissueComputeMetrics(),
            muscle_adipose_tissue_visualization.MuscleAdiposeTissueVisualizer(),
            muscle_adipose_tissue.MuscleAdiposeTissueH5Saver(),
            muscle_adipose_tissue.MuscleAdiposeTissueNiftiSaver(),
            muscle_adipose_tissue.MuscleAdiposeTissueMetricsSaver(),
        ]
    )
    return pipeline


def MuscleAdiposeTissueFullPipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [io.DicomFinder(path), MuscleAdiposeTissuePipelineBuilder(args)]
    )
    return pipeline


def SpinePipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            io.DicomToNifti(path),
            spine.SpineSegmentation(args.spine_model, save=True),
            orientation.ToCanonical(),
            spine.SpineComputeROIs(args.spine_model),
            spine.SpineMetricsSaver(),
            spine.SpineCoronalSagittalVisualizer(format="png"),
            spine.SpineReport(format="png"),
        ]
    )
    return pipeline


def AxialCropperPipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            io.DicomToNifti(path, "aaa"),
            spine.SpineSegmentation(args.spine_model),
            orientation.ToCanonical(),
            spine.AxialCropper(lower_level="L5", upper_level="L1", save=True),
        ]
    )
    return pipeline


def SpineMuscleAdiposeTissuePipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            SpinePipelineBuilder(path, args),
            spine.SpineFindDicoms(),
            MuscleAdiposeTissuePipelineBuilder(args),
            spine.SpineMuscleAdiposeTissueReport(),
        ]
    )
    return pipeline


def LiverSpleenPancreasPipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            io.DicomToNifti(path),
            liver_spleen_pancreas.LiverSpleenPancreasSegmentation(),
            orientation.ToCanonical(),
            liver_spleen_pancreas_visualization.LiverSpleenPancreasVisualizer(),
            liver_spleen_pancreas_visualization.LiverSpleenPancreasMetricsPrinter(),
        ]
    )
    return pipeline


def AorticCalciumPipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            io.DicomToNifti(path),
            spine.SpineSegmentation(model_name=args.spine_model),
            orientation.ToCanonical(),
            aortic_calcium.AortaSegmentation(),
            orientation.ToCanonical(),
            aortic_calcium.AorticCalciumSegmentation(),
            aortic_calcium.AorticCalciumMetrics(),
            aortic_calcium_visualization.AorticCalciumVisualizer(),
            aortic_calcium_visualization.AorticCalciumPrinter(),
        ],
        args=args
    )
    return pipeline


def ContrastPhasePipelineBuilder(path, args):
    pipeline = InferencePipeline([io.DicomToNifti(path), ContrastPhaseDetection(path)])
    return pipeline


def HipPipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            io.DicomToNifti(path),
            hip.HipSegmentation(args.hip_model),
            orientation.ToCanonical(),
            hip.HipComputeROIs(args.hip_model),
            hip.HipMetricsSaver(),
            hip.HipVisualizer(),
        ]
    )
    return pipeline


def AllPipelineBuilder(path, args):
    pipeline = InferencePipeline(
        [
            io.DicomToNifti(path),
            SpineMuscleAdiposeTissuePipelineBuilder(path, args),
            LiverSpleenPancreasPipelineBuilder(path, args),
            HipPipelineBuilder(path, args),
        ]
    )
    return pipeline


def argument_parser():
    base_parser = argparse.ArgumentParser(add_help=False)
    base_parser.add_argument("--input_path", "-i", type=str, required=True)
    base_parser.add_argument("--output_path", "-o", type=str)
    base_parser.add_argument("--save_segmentations", action="store_true")
    base_parser.add_argument("--overwrite_outputs", action="store_true")

    parser = argparse.ArgumentParser()
    subparsers = parser.add_subparsers(dest="pipeline", help="Pipeline to run")

    # Add the help option to each subparser
    muscle_adipose_tissue_parser = subparsers.add_parser(
        "muscle_adipose_tissue", parents=[base_parser]
    )
    muscle_adipose_tissue_parser.add_argument(
        "--muscle_fat_model", default="abCT_v0.0.1", type=str
    )

    # Spine
    spine_parser = subparsers.add_parser("spine", parents=[base_parser])
    spine_parser.add_argument("--spine_model", default="ts_spine", type=str)

    # Spine + muscle + fat
    spine_muscle_adipose_tissue_parser = subparsers.add_parser(
        "spine_muscle_adipose_tissue", parents=[base_parser]
    )
    spine_muscle_adipose_tissue_parser.add_argument(
        "--muscle_fat_model", default="stanford_v0.0.2", type=str
    )
    spine_muscle_adipose_tissue_parser.add_argument(
        "--spine_model", default="ts_spine", type=str
    )

    # Liver spleen pancreas
    liver_spleen_pancreas = subparsers.add_parser(
        "liver_spleen_pancreas", parents=[base_parser]
    )

    # Aortic calcium
    aortic_calcium = subparsers.add_parser(
        "aortic_calcium", parents=[base_parser])
    
    aortic_calcium.add_argument(
        "--threshold", default="adaptive", type=str
    )
    aortic_calcium.add_argument(
        "--spine-model", default="ts_spine", type=str, help='Chose the model to perfom the spine segmentation'
    )
    aortic_calcium.add_argument(
        "--mosaic-type", default='all', type=str, help='Chose the the type of axial mosaic in the overview image'
    )
    
    # Contrast phase
    contrast_phase_parser = subparsers.add_parser(
        "contrast_phase", parents=[base_parser]
    )

    hip_parser = subparsers.add_parser("hip", parents=[base_parser])
    hip_parser.add_argument(
        "--hip_model",
        default="ts_hip",
        type=str,
    )

    # AAA
    aorta_diameter_parser = subparsers.add_parser("aaa", help="aorta diameter", parents=[base_parser])

    aorta_diameter_parser.add_argument(
        "--aorta_model",
        default="ts_spine",
        type=str,
        help="aorta model to use for inference",
    )

    aorta_diameter_parser.add_argument(
        "--spine_model",
        default="ts_spine",
        type=str,
        help="spine model to use for inference",
    )

    all_parser = subparsers.add_parser("all", parents=[base_parser])
    all_parser.add_argument(
        "--muscle_fat_model",
        default="abCT_v0.0.1",
        type=str,
    )
    all_parser.add_argument(
        "--spine_model",
        default="ts_spine",
        type=str,
    )
    all_parser.add_argument(
        "--hip_model",
        default="ts_hip",
        type=str,
    )
    return parser


def main():
    args = argument_parser().parse_args()
    if args.pipeline == "spine_muscle_adipose_tissue":
        process_3d(args, SpineMuscleAdiposeTissuePipelineBuilder)
    elif args.pipeline == "muscle_adipose_tissue":
        process_3d(args, MuscleAdiposeTissueFullPipelineBuilder)
    elif args.pipeline == "spine":
        process_3d(args, SpinePipelineBuilder)
    elif args.pipeline == "contrast_phase":
        process_3d(args, ContrastPhasePipelineBuilder)
    elif args.pipeline == "liver_spleen_pancreas":
        process_3d(args, LiverSpleenPancreasPipelineBuilder)
    elif args.pipeline == "aortic_calcium":
        process_3d(args, AorticCalciumPipelineBuilder)
    elif args.pipeline == "hip":
        process_3d(args, HipPipelineBuilder)
    elif args.pipeline == "aaa":
        process_3d(args, AAAPipelineBuilder)
    elif args.pipeline == "all":
        process_3d(args, AllPipelineBuilder)
    else:
        raise AssertionError("{} command not supported".format(args.action))


if __name__ == "__main__":
    main()