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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

Medical image of the ventricles with the mean shape (computed during AAM model generation) superimposed. The AAM process searches for the target structures (ventricular blood masses) until convergence.
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Figure 4: Medical image of the ventricles with the mean shape (computed during AAM model generation) superimposed. The AAM process searches for the target structures (ventricular blood masses) until convergence.

Mentions: The search procedure starts after mean model insertion in the image data. In a next step the mean model gets initialized, which means to locate the left and right ventricular blood masses best possible only by using the mean model information. After this procedure the starting vector for the AAM search is defined. From the time when the initialization is done, the model fit approach (AAM search) starts until the search converges. Because the likelihood that the adjacent images have a related shape and gray-level appearance the finding of the prior arranged search is used as starting vector in the adjacent images. This approach is repeated from apex cordis up to the base of the heart. The approach extracts the separated blood masses of the left and right ventricle, as shown in Fig. (4).


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)

Medical image of the ventricles with the mean shape (computed during AAM model generation) superimposed. The AAM process searches for the target structures (ventricular blood masses) until convergence.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: Medical image of the ventricles with the mean shape (computed during AAM model generation) superimposed. The AAM process searches for the target structures (ventricular blood masses) until convergence.
Mentions: The search procedure starts after mean model insertion in the image data. In a next step the mean model gets initialized, which means to locate the left and right ventricular blood masses best possible only by using the mean model information. After this procedure the starting vector for the AAM search is defined. From the time when the initialization is done, the model fit approach (AAM search) starts until the search converges. Because the likelihood that the adjacent images have a related shape and gray-level appearance the finding of the prior arranged search is used as starting vector in the adjacent images. This approach is repeated from apex cordis up to the base of the heart. The approach extracts the separated blood masses of the left and right ventricle, as shown in Fig. (4).

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