Cardiac Atlases and Machine Learning for Heart Shape and Function Assessment

Alistair Young, Avan Suinesiaputra, Kathleen Gilbert, Charlène Alice Mauger1, Jeffrey Omens, Martyn Nash, Andrew Mcculloch2

  • 1University of Auckland
  • 2University of California San Diego





08:30 - 10:00 | Wed 24 Jul | M4 - Level 3 | WeA11

Challenges and Opportunities of Cardiac Imaging and Advanced Data Analysis in Cardiovascular Disease

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Machine learning algorithms enable automatic analysis of multidimensional data from medical imaging examinations and other clinical information. These methods can be combined with atlas-based analysis of heart geometry and function to give morphometric indices which are optimally associated with clinical factors. We describe methods which can be used to characterize patients with heart failure according to a rich set of morphological features which may give insight into the underlying pathological processes.

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