
Proceedings Paper
Constructing a 4D murine cardiac micro-CT atlas for automated segmentation and phenotyping applicationsFormat | Member Price | Non-Member Price |
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Paper Abstract
A number of investigators have demonstrated the potential of preclinical micro-CT in characterizing cardiovascular
disease in mouse models. One major hurdle to advancing this approach is the extensive user interaction required to
derive quantitative metrics from these 4D image arrays (space + time). In this work, we present: (1) a method for
constructing an average anatomic cardiac atlas of the mouse based on 4D micro-CT images, (2) a fully automated
approach for segmenting newly acquired cardiac data sets using the atlas, and (3) a quantitative characterization of atlas-based
segmentation accuracy and consistency. Employing the deformable registration toolkit, ANTs, the construction of
minimal deformation fields, and a novel adaptation of joint bilateral filtration, our atlas construction scheme was used to
integrate 6, C57BL/6 cardiac micro-CT data sets, reducing the noise standard deviation from ~70 HU in the individual
data sets to ~21 HU in the atlas data set. Using the segmentation tools in Atropos and our atlas-based segmentation, we
were able to propagate manual labels to 5, C57BL/6 data sets not used in atlas construction. Average Dice coefficients
and volume accuracies (respectively) over phases 1 (ventricular diastole), 3, and 5 (ventricular systole) of these 5 data
sets were as follows: left ventricle, 0.96, 0.96; right ventricle, 0.89, 0.92; left atrium, 0.88, 0.89; right atrium, 0.86, 0.92;
myocardium, 0.90, 0.94. Once the atlas was constructed and segmented, execution of the proposed automated
segmentation scheme took ~6.5 hours per data set, versus more than 50 hours required for a manual segmentation.
Paper Details
Date Published: 13 March 2013
PDF: 12 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86691P (13 March 2013); doi: 10.1117/12.2007043
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
PDF: 12 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86691P (13 March 2013); doi: 10.1117/12.2007043
Show Author Affiliations
D. Clark, Duke Univ. Medical Ctr. (United States)
A. Badea, Duke Univ. Medical Ctr. (United States)
A. Badea, Duke Univ. Medical Ctr. (United States)
G. A. Johnson, Duke Univ. Medical Ctr. (United States)
C. T. Badea, Duke Univ. Medical Ctr. (United States)
C. T. Badea, Duke Univ. Medical Ctr. (United States)
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
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