11.14. Clara AI Prostate Segmentation Pipeline

            

            
api-version: 0.4.0
name: prostate-pipeline
operators:
# dicom reader operator
# Input: '/input' mapped directly to the input of the pipeline, which is populated by the DICOM Adaptor.
# Output:'/output' for saving converted volume image in MHD format to file whose name
#            is the same as the DICOM series instance ID.
- name: dicom-reader
  description: Converts DICOM instances into MHD, one file per DICOM series.
  container:
    image: clara/dicom-reader
    tag: latest
  input:
  - path: /input
  output:
  - path: /output
# prostate-segmentation operator
# Input: `/input` containing volume image data, MHD format, with a single volume.
# Output: `/output` containing segmented volume image, MHD format.
#         `/publish` containing original and segmented volume images, MHD format,
#             along with rendering configuration file.
- name: prostate-segmentation
  description: Segmentation of prostate using DL trained model.
  container:
    image: clara/ai-prostate
    tag: latest
  input:
  - from: dicom-reader
    path: /input
  output:
  - path: /output
    name: segmentation
  - path: /publish
    name: rendering
  - path: /logs
    name: logs
  services:
  - name: trtis
  # Triton Inference Server, required by this AI application.
    container:
      image: nvcr.io/nvidia/tritonserver
      tag: 20.07-v1-py3
      command: ["tritonserver", "--model-repository=$(NVIDIA_CLARA_SERVICE_DATA_PATH)/models"]
    # services::connections defines how the TRTIS service is expected to
    # be accessed. Clara Platform supports network ("http") and
    # volume ("file") connections.
    connections:
      http:
      # The name of the connection is used to populate an environment
      # variable inside the operator's container during execution.
      # This AI application inside the container needs to read this variable to
      # know the IP and port of TRTIS in order to connect to the service.
      - name: NVIDIA_CLARA_TRTISURI
        port: 8000
      # Some services need a specialized or minimal set of hardware. In this case
      # NVIDIA Tensor RT Inference Server [TRTIS] requires at least one GPU to function.
# dicom writer operator
# Input1: `/input` containing a volume image file, in MHD format, name matching the DICOM series instance UID.
# Input2: `/dicom` containing original DICOM instances, i.e. dcm file.
# Output: `/output` containing the DICOM instances converted from the volume image, with updated attributes
#         based on original DICOM instances.
- name: dicom-seg-writer
  description: Converts MHD into DICOM instance with attributes based on the original instances.
  container:
    image: clara/dicom-seg-writer
    tag: latest
  variables:
    NVIDIA_SEG_LABELS: "[\"Prostate\"]"
  input:
  - from: prostate-segmentation
    name: segmentation
    path: /input
  - path: /dcm
  output:
  - path: /output
    name: dicom
  - path: /logs
    name: logs
# dicom RTSTRUCT writer operator
# Input1: `/input` containing a volume image file, in MHD format.
# Input2: `/dcm` containing original DICOM instances, i.e. dcm files.
# Output: `/output` containing the DICOM RT Structure Set instance for the segmentation mask contours,
#         with attributes referring to the original DICOM Series.
- name: rtstruct-writer
  description: Converts MHD into DICOM RTSTRUCT instance with attributes rfererring to the original instances.
  container:
    image: clara/rtstruct_writer
    tag: latest
  input:
  - from: prostate-segmentation
    name: segmentation
    path: /input
  - path: /dcm
  output:
  - path: /output
    name: dicom
  - path: /logs
    name: logs
# register-volume-images-for-rendering operator
# Input: Published original and segmented volume images, MHD format, along with rendering configuration file
#        from the segmentation operator.
# Output: N/A. Input data will be sent to the destination, namely `renderserver` for Render Server DataSet Service.
- name: register-volume-images-for-rendering
  description: Register volume images, MHD format, for rendering.
  container:
    image: clara/register-results
    tag: latest
    command: ["python", "register.py", "--agent", "renderserver"]
  input:
  - from: prostate-segmentation
    name: rendering
    path: /input
# register-dicom-output operator
# Input: `/input` containing DICOM instances in the named output, `dicom` from dicom-seg-writer operator.
# Output: N/A. Input data will be sent to the destinations, namely DICOM devices, by the Clara DICOM SCU agent.
- name: register-dicom-output
  description: Register converted DICOM instances with Results Service to be sent to external DICOM devices.
  container:
    image: clara/register-results
    tag: latest
    command: ["python", "register.py", "--agent", "ClaraSCU", "--data", "[\"MYPACS\"]"]
  input:
  - from: dicom-seg-writer
    name: dicom
    path: /input
# register-dicom-RTSTRUCT-output operator
# Input: `/input` containing DICOM instance in the named output, `dicom` from rtstruct-writer operator.
# Output: N/A. Input data will be sent to the destinations, namely DICOM devices, by the Clara DICOM SCU agent.
- name: register-dicom-rtstruct-output
  description: Register converted DICOM RTSTRUCT instance with Results Service to be sent to external DICOM devices.
  container:
    image: clara/register-results
    tag: latest
    command: ["python", "register.py", "--agent", "ClaraSCU", "--data", "[\"MYPACS\"]"]
  input:
  - from: rtstruct-writer
    name: dicom
    path: /input