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Ultrasound Sample App Data

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Description

Clara Holoscan Sample App Data for AI Ultrasound Segmentation for Scoliosis

Publisher

NVIDIA

Use Case

Other

Framework

Other

Latest Version

20220608

Modified

June 17, 2022

Compressed Size

133.09 MB

Clara Holoscan Sample App Data for AI-based Bone Scoliosis Segmentation

Overview

This resource contains the spine ultrasound segmentation model for scoliosis visualization and measurement developed by Richard Brown at King's College London, and an ultrasound video dataset from T. Ungi et al. (2020).

The AI model expects a gray-scale image of 256 x 256 and outputs a semantic segmentation of the same size with two channels representing

  • bone contours with hyperechoic lines (foreground),
  • hyperechoic acoustic shadow (background).

Refer to the Clara Holoscan Embedded SDK GitHub repository for details on how the sample app data is utilized.

Model

Inputs

  • INPUT__0 - Graysale ultrasound input image
    • shape=[3, 256, 256]
    • dtype=float32
    • range=[0,1]

Outputs

  • OUTPUT__0 - 2-channel semantic segmentation of ultrasound image (hyperechoic lines, hyperechoic accoustic shadow)
    • shape=[2, 256, 256]
    • dtype=float32
    • range=[0,1]

Directory Structure

The package contains two folders:

  • the model folder with the source model in ONNX format, and .engine files for the TensorRT models optimized for the Clara AGX and Holoscan developer kits.
  • the video folder with the recorded video data, both in mp4 (source) and converted to the NVIDIA GXF tensor format.
/
├── LICENSE.md
├── NVIDIA-Clara-Holoscan-SDK-EULA.pdf
├── model
│   ├── us_unet_256x256_nhwc.onnx
│   └── us_unet_256x256_nhwc_engines
│       ├── NVIDIA-RTX-A6000_c86_n84.engine
│       └── Quadro-RTX-6000_c75_n72.engine
└── video
    ├── ultrasound_256x256.avi
    ├── ultrasound_256x256.gxf_entities
    └── ultrasound_256x256.gxf_index

License

Refer to LICENSE.md supplied within, and to the NVIDIA-Clara-Holoscan-SDK-EULA.pdf license agreement for use of the sample data.