Biomedical Image Computing Laboratory

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Advanced computational methods for automated biomedical image analysis, health informatics and downstream data analytics to improve the reliability and throughput of imaging-and multimodal data-based diagnostics and screening.

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Competitive advantage

  • Over 50 years’ combined experience in automated biomedical image analysis and health informatics
  • Multidisciplinary R&D in biomedical image computing, visual analytics and biomedical health informatics

Impact

  • Early screening and faster, more accurate diagnosis of chronic diseases
  • Facilitating the discovery of imaging biomarkers
  • Advancing the understanding of brain function in health and disorders
  • Support for radiotherapy planning and distributed learning in medical settings
  • High-throughput image analytics for drug screening

Successful outcomes

  • Software for atherosclerotic carotid plaque quantification
  • Automated vessel analysis for diagnosis of cardiovascular diseases
  • Framework for quantitative analysis of ocular images
  • Diffuse lung disease feature recognition and quantification
  • Pattern recognition methods for digital histopathology
  • Motion artefact removal in digital angiography
  • CAD for diffuse lung disease pattern recognition
  • 3-D image analysis for the improved treatment of arterio-venous malformations (AVMs)

Capabilities and facilities

  • Machine and Deep learning
  • GPU-based high-performance computing
  • Imaging across the EM spectrum-radio waves to X-rays

Our partners

  • Harvard Medical School
  • Technical University, Munich
  • Geneva Neuroscience Center, University of Geneva
  • Prince of Wales Hospital, Sydney
  • Royal Women’s Hospital, Sydney