Algorithms for Mapping Elastic Modulus (aMEM) Challenge
Elastographic imaging (or elastography) is a powerful, non-invasive, and multiscale technique that can measure the biomechanical properties of tissues. The rapidly expanding interest in elastography in both clinical and preclinical medical research domains, reflects its potential, not only to improve the detection and diagnosis of disease, but also to help understand the underlying mechanobiological mechanisms that promote disease. We challenged the elastographic imaging research community to analyse shear wave data to produce elastograms, which were evaluated for image quality. This paper describes the aims of the challenge, the structure of the challenge, the entries and gives a brief description of how the submissions were evaluated.
Authors
- Matthew W. Urban (ORCID: https://orcid.org/0000-0003-1360-4287)
- Jeffrey C. Bamber (ORCID: https://orcid.org/0000-0001-9436-1832)
- Emma Harris (ORCID: https://orcid.org/0000-0001-8297-0382)
- Tom Meyer (ORCID: https://orcid.org/0000-0002-2171-6791)
- Mark L. Palmeri (ORCID: https://orcid.org/0000-0001-8995-0050)
- John Civale (ORCID: https://orcid.org/0000-0002-9014-9292)
- Heiko Tzschaetzsch
Institutions
- Mayo Clinic (US)
- Institute of Cancer Research (GB)
- Duke University (US)
Publication Details
- Published
- 2024-09-22
- DOI
- https://doi.org/10.1109/uffc-js60046.2024.10793812
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Cancer Research UK
- Institute of Cancer Research
- HORIZON EUROPE Health