Automated Segmentation and 4D Reconstruction of the Heart Left Ventricle from CINE MRI

Giovanni Molina, Jose D. Velazco-Garcia, Dipan J. Shah, Aaron T. Becker, Ioannis Seimenis, Panagiotis Tsiamyrtzis, Nikolaos V. Tsekos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Heart disease is highly prevalent in developed countries, causing 1 in 4 deaths. In this work we propose a method for a fully automated 4D reconstruction of the left ventricle of the heart. This can provide accurate information regarding the heart wall motion and in particular the hemodynamics of the ventricles. Such metrics are crucial for detecting heart function anomalies that can be an indication of heart disease. Our approach is fast, modular and extensible. In our testing, we found that generating the 4D reconstruction from a set of 250 MRI images takes less than a minute. The amount of time saved as a result of our work could greatly benefit physicians and cardiologist as they diagnose and treat patients.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1019-1023
Number of pages5
ISBN (Electronic)9781728146171
DOIs
StatePublished - Oct 1 2019
Event19th International Conference on Bioinformatics and Bioengineering, BIBE 2019 - Athens, Greece
Duration: Oct 28 2019Oct 30 2019

Other

Other19th International Conference on Bioinformatics and Bioengineering, BIBE 2019
CountryGreece
CityAthens
Period10/28/1910/30/19

Keywords

  • Cardiac
  • Heart
  • Machine learning
  • Magnetic Resonance Imaging
  • Reconstruction
  • Segmentation
  • Ventricle

ASJC Scopus subject areas

  • Information Systems
  • Biomedical Engineering
  • Health Informatics

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