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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

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AAM-based segmentation for imaging cardiac electrophysiology.

B Pfeifer¹, M Seger, C Hintermüller

¹Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i.T., Austria. bernhard.pfeifer@umit.at

Methods of Information in Medicine

|January 17, 2007

Summary

This study introduces a novel method using Active Appearance Models (AAMs) to extract cardiac blood masses from MRI data for non-invasive activation time (AT) imaging. This approach facilitates semi-automatic processing for advanced cardiac electrical activity analysis.

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Published on: January 31, 2019

Area of Science:

Cardiovascular Imaging
Computational Cardiology
Medical Image Analysis

Background:

Activation time (AT) imaging aims to non-invasively compute cardiac electrical sequences using electrocardiographic (ECG) mapping data.
Accurate extraction of cardiac blood masses is crucial for reliable AT imaging.

Purpose of the Study:

To introduce a novel approach for extracting ventricular and atrial blood masses from cine-gated short-axis MRI data.
To enable semi-automatic processing for AT imaging in structurally normal hearts.

Main Methods:

Active Appearance Models (AAMs) were employed to segment ventricular and atrial blood masses.
The atria were divided into three divisions to handle their complex geometry.
Extracted cardiac blood masses were triangulated and remeshed for AT imaging.

Main Results:

Cardiac models of eight patients were successfully extracted using the proposed method.
The AT imaging approach was applied to single-beat ECG data for atrial and ventricular depolarization.
The method demonstrated the feasibility of semi-automatic extraction of cardiac structures.

Conclusions:

The proposed AAM approach requires minimal initial parameter setting, enabling semi-automatic integration into processing pipelines.
The extracted cardiac models are suitable for further detailed investigations in electrophysiology.
This method advances non-invasive cardiac electrical mapping techniques.