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Abstract 11962 : Applying a Deep-Learning Approach for Automated Quantification of Epicardial Adipose Tissue on Coronary Computed Tomography Angiography in Challenging Clinical Populations

Researchers

Presenter

  • Henry W West

Principal Investigators

  • Muhammad Siddique

  • Lucrezia Volpe

  • Ria Desai

  • Maria Lyasheva

  • Katerina Dangas

  • Cheerag Shirodaria

  • Stefan Neubauer

  • Keith M Channon

  • Milind Y Desai

  • Michelle C Williams

  • Jonathan C Rodrigues

  • David Adlam

  • Nicol D Ed

  • Charalambos Antoniades

Medical Centers

  • Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom

  • Blue Earth Diagnostics, Oxford, United Kingdom

  • Univ of Oxford, Oxford

  • Northwestern University, Chicago, IL

  • Cleveland, OH

  • Royal United Hosp Bath NHS Trust, Bath, United Kingdom

  • Royal Brompton and Harefield NHS Foundation Trust, London, United Kingdom

  • The University of Edinburgh, Edinburgh, United Kingdom

  • Univ of Leicester, Leicester

Locations

  • United Kingdom

  • United States

Companies

  • N/A

Study Components

Therapeutic Area

  • Cardiovascular (CVS)

Disease

  • Angina

Biomarkers

  • Carbonic anhydrase II

  • Body mass index

Drug/Treatment

  • N/A

Outcome

  • N/A

Study Design

  • N/A

Phase

  • NA

Study Id's

  • N/A

Sponsors

  • N/A

Result

  • N/A

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