A Fast Greedy Sparse Method of Current Sources Reconstruction for Ventricular Torsion Detection
Creators
- 1. Department of Control Science and Engineering, School of Electronics and Information Engineering, Tongji University, Shanghai 201804 (China)
- 2. Departments of Biomagnetism, Grönemeyer Institute for Microtherapy, Faculty of Health, University Witten/Herdecke, Bochum D-44799 (Germany)
- 3. Department of Internal Medicine, Philippusstift, University Witten/Herdecke, Essen (Germany)
Description
A fast greedy sparse (FGS) method of cardiac equivalent current sources reconstruction is developed for non-invasive detection and quantitative analysis of individual left ventricular torsion. The cardiac magnetic field inverse problem is solved based on a distributed source model. The analysis of real 61-channel magnetocardiogram (MCG) data demonstrates that one or two dominant current source with larger strength can be identified efficiently by the FGS algorithm. Then, the left ventricle torsion during systole is examined on the basis of x, y and z coordination curves and angle change of reconstructed dominant current sources. The advantages of this method are non-invasive, visible, with higher sensitivity and resolution. It may enable the clinical detection of cardiac systolic and ejection dysfunction. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1742-6596/633/1/012138Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Physics. Conference Series (Online)
- Journal Volume
- 633
- Journal Issue
- 1
- Journal Page Range
- [4 p.]
- ISSN
- 1742-6596
Conference
- Title
- 4. international conference on mathematical modeling in physical sciences
- Acronym
- IC-MSquare2015
- Dates
- 5-8 Jun 2015
- Place
- Mykonos (Greece)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 47098443
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; S60: APPLIED LIFE SCIENCES;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- ALGORITHMS; CARDIOGRAPHY; DETECTION; DIAGRAMS; ELECTRIC CURRENTS; MAGNETIC FIELDS; MATHEMATICAL MODELS; RESOLUTION; SENSITIVITY; TORSION
- Descriptors DEC
- CURRENTS; DIAGNOSTIC TECHNIQUES; INFORMATION; MATHEMATICAL LOGIC