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Patient-specific volume conductor modeling for non-invasive imaging of cardiac electrophysiology.

Pfeifer B, Hanser F, Seger M, Fischer G, Modre-Osprian R, Tilg B - Open Med Inform J (2008)

Bottom Line: We propose a general workflow to numerically estimate the spread of electrical excitation in the patients' hearts.The non-invasive estimation of electrical excitation was compared with the CARTO maps.The development of a volume conductor modeling pipeline for constructing a patient-specific volume conductor model in a fast and accurate way is one essential step to make the technique clinically applicable.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i.T., Austria.

ABSTRACT
We propose a general workflow to numerically estimate the spread of electrical excitation in the patients' hearts. To this end, a semi-automatic segmentation pipeline for extracting the volume conductor model of structurally normal hearts is presented. The cardiac electrical source imaging technique aims to provide information about the spread of electrical excitation in order to assist the cardiologist in developing strategies for the treatment of cardiac arrhythmias. The volume conductor models of eight patients were extracted from cine-gated short-axis magnetic resonance imaging (MRI) data. The non-invasive estimation of electrical excitation was compared with the CARTO maps. The development of a volume conductor modeling pipeline for constructing a patient-specific volume conductor model in a fast and accurate way is one essential step to make the technique clinically applicable.

No MeSH data available.


Related in: MedlinePlus

The left figure shows the chest segmentation algorithm where the algorithm fails to separate the right arm (at the left position in the left image). The right figure shows the first image in the volume data where the chest segmentation algorithm is able remove both arms in order to extract a symmetric chest model.
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Figure 3: The left figure shows the chest segmentation algorithm where the algorithm fails to separate the right arm (at the left position in the left image). The right figure shows the first image in the volume data where the chest segmentation algorithm is able remove both arms in order to extract a symmetric chest model.

Mentions: In the next step the algorithm searches the position of the image where the chest’s border appear for the first time. This row position is the starting vector for extracting the chest and separating the arms. Therefore, on the most left and most right voxel of the initial position a beam with a 45 degree angle is projected to the chests border. After this projection the left beam tries to reach the last row of the image by following the left border of the chest. The left image in Fig. (3) shows an example where the algorithm was able to separate only one arm, which means that both arms remain part of the model. The right image in Fig. (3) shows the algorithm succeeding in separating both arms. From now on, the arms are separated and cut off in the model. Although this separating procedure is not crucial for our estimation of the electrical excitation in the human heart approach, it helps generate symmetric models.


Patient-specific volume conductor modeling for non-invasive imaging of cardiac electrophysiology.

Pfeifer B, Hanser F, Seger M, Fischer G, Modre-Osprian R, Tilg B - Open Med Inform J (2008)

The left figure shows the chest segmentation algorithm where the algorithm fails to separate the right arm (at the left position in the left image). The right figure shows the first image in the volume data where the chest segmentation algorithm is able remove both arms in order to extract a symmetric chest model.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2666958&req=5

Figure 3: The left figure shows the chest segmentation algorithm where the algorithm fails to separate the right arm (at the left position in the left image). The right figure shows the first image in the volume data where the chest segmentation algorithm is able remove both arms in order to extract a symmetric chest model.
Mentions: In the next step the algorithm searches the position of the image where the chest’s border appear for the first time. This row position is the starting vector for extracting the chest and separating the arms. Therefore, on the most left and most right voxel of the initial position a beam with a 45 degree angle is projected to the chests border. After this projection the left beam tries to reach the last row of the image by following the left border of the chest. The left image in Fig. (3) shows an example where the algorithm was able to separate only one arm, which means that both arms remain part of the model. The right image in Fig. (3) shows the algorithm succeeding in separating both arms. From now on, the arms are separated and cut off in the model. Although this separating procedure is not crucial for our estimation of the electrical excitation in the human heart approach, it helps generate symmetric models.

Bottom Line: We propose a general workflow to numerically estimate the spread of electrical excitation in the patients' hearts.The non-invasive estimation of electrical excitation was compared with the CARTO maps.The development of a volume conductor modeling pipeline for constructing a patient-specific volume conductor model in a fast and accurate way is one essential step to make the technique clinically applicable.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i.T., Austria.

ABSTRACT
We propose a general workflow to numerically estimate the spread of electrical excitation in the patients' hearts. To this end, a semi-automatic segmentation pipeline for extracting the volume conductor model of structurally normal hearts is presented. The cardiac electrical source imaging technique aims to provide information about the spread of electrical excitation in order to assist the cardiologist in developing strategies for the treatment of cardiac arrhythmias. The volume conductor models of eight patients were extracted from cine-gated short-axis magnetic resonance imaging (MRI) data. The non-invasive estimation of electrical excitation was compared with the CARTO maps. The development of a volume conductor modeling pipeline for constructing a patient-specific volume conductor model in a fast and accurate way is one essential step to make the technique clinically applicable.

No MeSH data available.


Related in: MedlinePlus