Methods Inf Med 2006; 45(01): 19-26
DOI: 10.1055/s-0038-1634032
Original Article
Schattauer GmbH

Atrial and Ventricular Myocardium Extraction Using Model-based Techniques

B. Pfeifer
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
,
G. Fischer
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
,
F. Hanser
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
,
M. Seger
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
,
C. Hintermüller
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
,
R. Modre-Osprian
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
,
T. Trieb
2   Clinical Division of Diagnostic Radiology I, Innsbruck Medical University, Innsbruck, Austria
,
B. Tilg
1   Institute for Biomedical Signal Processing and Imaging, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall i. T., Austria
› Author Affiliations
Further Information

Publication History

Publication Date:
06 February 2018 (online)

Summary

Objectives: This paper presents an efficient approach for extracting myocardial structures from given atrial and ventricular blood masses to enable non-invasive estimation of electrical excitation in human atria and ventricles.

Methods: Based on given segmented atrial and ventricular blood masses, the approach constructs the myocardial structure directly, in the case that the myocardium can be detected in the volume data, or by using mean model information, in the case that the myocardium cannot be seen in the volume data due to image modalities or artefacts. The approach employs mathematical and gray-value morphology operations. Regulated by the spatial visibility of the myocardial structure in the medical image data especially the atrial myocardium needs to be estimated repeatedly using the a-priori knowledge given by the anatomy.

Results: The approach was tested using eight patient data sets. The reconstruction process yielded satisfying results with respect to an efficient generation of a volume conductor model which is essential when trying to implement the estimation of electrical excitation in clinical application.

Conclusion: The approach yields ventricular and atrial models that qualify for cardiac source imaging in a clinical setting.

 
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