CemrgApp: An interactive medical imaging application with image processing, computer vision, and machine learning toolkits for cardiovascular research.

Journal: SoftwareX
Published Date:

Abstract

Personalised medicine is based on the principle that each body is unique and will respond to therapies differently. In cardiology, characterising patient specific cardiovascular properties would help in personalising care. One promising approach for characterising these properties relies on performing computational analysis of multimodal imaging data. An interactive cardiac imaging environment, which can seamlessly render, manipulate, derive calculations, and otherwise prototype research activities, is therefore sought-after. We developed the Cardiac Electro-Mechanics Research Group Application (CemrgApp) as a platform with custom image processing and computer vision toolkits for applying statistical, machine learning and simulation approaches to study physiology, pathology, diagnosis and treatment of the cardiovascular system. CemrgApp provides an integrated environment, where cardiac data visualisation and workflow prototyping are presented through a common graphical user interface.

Authors

  • Orod Razeghi
    King's College London, London, United Kingdom.
  • José Alonso Solís-Lemus
    King's College London, London, United Kingdom.
  • Angela W C Lee
    King's College London, London, United Kingdom.
  • Rashed Karim
    King's College London, London, United Kingdom.
  • Cesare Corrado
    King's College London, London, United Kingdom.
  • Caroline H Roney
    King's College London, London, United Kingdom.
  • Adelaide de Vecchi
    King's College London, London, United Kingdom.
  • Steven A Niederer
    Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom.

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