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Automatic quantification of epicardial fat volume on non-enhanced cardiac CT scans using a multi-atlas segmentation approach
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10.1118/1.4817577
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    Affiliations:
    1 Quantitative Imaging Group, Faculty of Applied Sciences, Delft University of Technology, 2628 CJ Delft, The Netherlands and Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    2 Department of Radiology, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands and Department of Epidemiology, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    3 Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    4 Department of Radiology, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    5 Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    6 Department of Radiology, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    7 Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    8 Department of Epidemiology, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    9 Department of Radiology, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    10 Quantitative Imaging Group, Faculty of Applied Sciences, Delft University of Technology, 2628 CJ Delft, The Netherlands and Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    11 Quantitative Imaging Group, Faculty of Applied Sciences, Delft University of Technology, 2628 CJ Delft, The Netherlands
    12 Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam, The Netherlands
    a) Electronic mail: R.Shahzad@tudelft.nl
    Med. Phys. 40, 091910 (2013); http://dx.doi.org/10.1118/1.4817577
/content/aapm/journal/medphys/40/9/10.1118/1.4817577
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/40/9/10.1118/1.4817577

Figures

Image of FIG. 1.
FIG. 1.

Overview of the segmentation process. Top left: Eight CTA atlas scans and the corresponding manually segmented 3D surfaces. Top right: CT scan to be segmented. The atlas scans are registered and the 3D surfaces are transformed to match the subject scan. Bottom right: The 3D surfaces are combined using majority voting. Bottom left: Resulting fat voxels, obtained after thresholding and connected component analysis.

Image of FIG. 2.
FIG. 2.

The eight pericardium atlas surfaces used for atlas-based segmentation illustrating the encountered shape and size variations in the atlas images.

Image of FIG. 3.
FIG. 3.

(a) A random axial slice showing the result of a manually obtained whole heart segmentation (with adjusted windowing level, for better visibility). (b) Corresponding slice showing the voxels containing epicardial fat.

Image of FIG. 4.
FIG. 4.

Random axial slice with the overlay representing the fixed mask used for the registration.

Image of FIG. 5.
FIG. 5.

Scatter plots of automatic vs manual fat quantification methods and results from linear regression: (a) correlation between the two observers; (b) correlation between Observer 1 and the automatic method; and (c) correlation between Observer 2 and the automatic method.

Image of FIG. 6.
FIG. 6.

Bland–Altman analysis: (a) between observers; (b) between automatic method and Observer 1; and (c) between automatic method and Observer 2.

Image of FIG. 7.
FIG. 7.

Excluded subjects: (a) subject with lung removed and (b) segmentation leaking into the ribcage due to rare anatomical variation in heart shape.

Tables

Generic image for table
TABLE I.

Characteristics of the subjects ( = 98). Values are mean ± SD for continuous variables and numbers (%) for dichotomous variables.

Generic image for table
TABLE II.

Table representing the results of the registration strategy. Values represent mean ± SD.

Generic image for table
TABLE III.

Performance of the whole heart segmentation: comparing the automatic method to each of the observers and the observers to each other.

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/content/aapm/journal/medphys/40/9/10.1118/1.4817577
2013-08-12
2014-04-17
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Automatic quantification of epicardial fat volume on non-enhanced cardiac CT scans using a multi-atlas segmentation approach
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/40/9/10.1118/1.4817577
10.1118/1.4817577
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