Clara Deploy SDK is being consolidated into Clara Holoscan SDK

More info https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/collections/claradeploy

Clara Chest X-ray Classification Pipeline

This asset requires the Clara Deploy SDK. Follow the instructions on the Clara Ansible page to install the Clara Deploy SDK.

Overview

The Chest X-ray Classification pipeline is one of the reference pipelines provided with Clara Deploy SDK. A pre-trained model for classification of diseases from a chest x-ray 16-bit PNG image is used in the pipeline. This pipeline depends on the Clara Deploy CLI to send a PNG image and trigger a job.

Once the pipeline is started, the AI model classifies an input image and saves the output as a new image with the classification label with probability burnt-in on top of the image. The model supports 15 categories ('Nodule', 'Mass', 'Distortion of Pulmonary Architecture', 'Pleural Based Mass', 'Granuloma', 'Fluid in Pleural Space', 'Right Hilar Abnormality', 'Left Hilar Abnormality', 'Major Atelectasis', 'Infiltrate', 'Scarring', 'Pleural Fibrosis', 'Bone/Soft Tissue Lesion', 'Cardiac Abnormality', and 'COPD'). The class categories with the probability are burnt to the upper left corner of the output image for top 3 categories. If the probability is high enough (0.5), the category is written out with red color, or yellow color is used. The name of each output file has the pattern output-<original file name>.png. It also outputs a CSV file (output-<original file name>.csv) including the input file path and top 3 classifications with probability (e.g., Granuloma:0.68,Nodule:0.22,COPD:0.02)

The output image can be downloaded by Clara CLI and viewed by any PNG image viewer such as GIMP.

Pipeline Definition

The Chest X-ray Classification pipeline is defined in the Clara Deploy pipeline definition language. This pipeline utilizes built-in reference containers to construct the following operator:

The ai-app-chestxray operator performs AI inference against the NVIDIA Triton Inference server to generate an image for disease classifications from a chest x-ray image.

The following is the details of pipeline definition, with comments describing each operator's functions as well as input and output.

api-version: 0.4.0
name: chestxray-pipeline
operators:
  - name: ai-app-chestxray
    description: Classifying Chest X-ray Images
    container:
      image: clara/ai-chestxray
      tag: latest
    requests:
      memory: 4096
    input:
    - path: /input
    output:
    - path: /output
    models:
    # change the following line to match the name created for the model
    - name: classification_chestxray_v1

Executing the Pipeline

Please refer to the Quick Start Guide section on how to run this reference pipeline using local input files.

Datasets

The model was trained using NIH PLCO data and a sample image is provided from another open dataset with some modification (8 bits to 16 bits image).

For any positive classification, user may need to acquire the data from NIH PLCO dataset.

License

An End User License Agreement is included with the product. By pulling and using the Clara Deploy asset on NGC, you accept the terms and conditions of these licenses.