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A lightweight rapid application development framework for biomedical image analysis.

Shekhar S Chandra1, Jason A Dowling2, Craig Engstrom3

  • 1School of Information Technology and Electrical Engineering, The University of Queensland, Australia.

Computer Methods and Programs in Biomedicine
|September 10, 2018
PubMed
Summary
This summary is machine-generated.

The Simple Medical Imaging Library Interface (SMILI) is an open-source framework for developing biomedical imaging applications. It enables rapid development and deployment of clinical tools, demonstrating high reliability in analyzing 3D MR images for femoro-acetabular impingement.

Keywords:
Biomedical SoftwareCam LesionsFAIITKImage AnalysisSMILIScientific VisualizationVTK

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Area of Science:

  • Biomedical Imaging Analysis
  • Medical Software Development
  • Radiological Applications

Background:

  • Biomedical imaging analysis involves complex tasks and requires robust software for clinical adoption.
  • Integrating research innovations into medical settings necessitates effective software deployment and evaluation.
  • Existing software packages can be overly complex for certain clinical applications.

Purpose of the Study:

  • Introduce the Simple Medical Imaging Library Interface (SMILI), an open-source framework for biomedical imaging application development.
  • Demonstrate SMILI's capabilities in creating a clinical tool for analyzing femoro-acetabular impingement (FAI) from 3D MR images.
  • Highlight SMILI's suitability for rapid prototyping and deployment of interactive biomedical imaging applications.

Main Methods:

  • Developed SMILI, an object-oriented, open-source framework supporting cross-platform biomedical imaging application development.
  • Utilized SMILI to create a clinical application for manual measurement of cam-type lesions in the femoral head-neck region from 3D MR hip images.
  • Compared SMILI's features and capabilities against existing state-of-the-art biomedical imaging software.

Main Results:

  • SMILI facilitates the development of both command-line and graphical applications using a unified set of algorithms.
  • The developed FAI analysis application demonstrated high intra-observer (ICC=0.97) and inter-observer (ICC=0.95) reliability in measuring α-angles.
  • SMILI offers a balance of features and compactness, suitable for clinical deployment with limited overhead and a commercial-use license.

Conclusions:

  • SMILI is a versatile, open-source framework well-suited for rapid prototyping and deployment of biomedical imaging applications.
  • The framework supports interactive applications and visualization of complex data, including 3D meshes and tensor data.
  • SMILI facilitates the adoption of research innovations by providing a deployable and reliable software solution for clinical partners.