MITEA or (MR-Informed Three-dimensional Echocardiography Analysis) dataset consists of annotated 3D echocardiography (3DE) data using labels derived from paired CMR scans acquired in a mixed cohort of 134 human subjects (82 healthy controls and 52 patients with acquired cardiac disease). For each subject, two 3DE scans (scan and rescan, in a randomised order) are available, at 2 image frames corresponding to end-diastole and end-systole. For each image, segmentations are also provided. Labelled regions are of the left ventricular myocardium (class value 1) and cavity (class value 2), which can be used for the quantification of LV systolic function and mass. A pre-trained deep learning model (based on nnU‑Net) is also made available upon request.

For additional dataset characteristics and preliminary model validation, researchers are referred to the original publication:

Zhao, D., Ferdian, E., Maso Talou, G. D., Gilbert, K., Quill, G. M., Wang, V. Y., Babarenda Gamage, T. P., Pedrosa, J., D’hooge, J., Sutton, T. M., Lowe, B. S., Legget, M. E., Ruygrok, P. N., Doughty, R. N., Young, A. A., Nash, M. P. (2023). MITEA: A dataset for segmentation of the left ventricle in 3D echocardiography using subject-specific labels from cardiac magnetic resonance imaging. Frontiers in Cardiovascular Medicine. Vol. 9, p. 3673.


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Intellectual Property Notice

The MITEA dataset, including the content, software and methodologies supported and detailed on the website, and all intellectual property rights subsisting in them, are and remain the property of the University of Auckland. Access to MITEA is provided strictly to the person(s) to whom access is provided by the University. No part of the MITEA dataset may be copied, or distributed or disclosed to any other person(s) without consent. MITEA can be provided under a non-commercial license CC BY-NC-SA 4.0 for research purposes. For commercial or other use, please contact the Data Contributors.


  1. Martyn Nash – University of Auckland, New Zealand
  2. Alistair Young – King’s College London, UK
  3. Debbie Zhao – University of Auckland, New Zealand


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