Abstract
Accurate segmentation of the whole heart from 3D image sequences is an important step in the developement of clinical applications. As manual delineation is a tedious task that is prone to errors and dependant on the expertise of the observer, fully automated segmentation methods are highly desirable. In this work, we present a fully automated method for the segmentation of the whole heart and the great vessels from 3D images. The method is based on a muti-atlas propagation segmentation scheme, that has been proven to be succesful in brain segmentation. Based on a cross correlation metric, our method selects the best atlases for propagation allowing the refinement of the segmentation at each iteration of the propagation. We show that our method allows segmentation from multiple image modalities by validating it on computed tomography angiography (CTA) and magnetic resonance images (MRI). Our results are comparable to state-of-the-art methods on CTA and MRI with average Dice scores of 90.9% and 89.0% for the whole heart when evaluated on a 23 and 8 cases, respectively.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Petitjean, C., Dacher, J.-N.: A review of segmentation methods in short axis cardiac MR images. Med. Image Anal. 15(2), 169–184 (2011)
Zheng, Y., Barbu, A., Georgescu, B., Scheuering, M., Comaniciu, D.: Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features. IEEE Transactions on Medical Imaging 27(11), 1668–1681 (2008)
Peters, J., Ecabert, O., Meyer, C., Kneser, R., Weese, J.: Optimizing boundary detection via Simulated Search with applications to multi-modal heart segmentation. Medical Image Analysis 14(1), 70–84 (2010)
Išgum, I., Staring, M., Rutten, A., Prokop, M., Viergever, M., van Ginneken, B.: Multi-Atlas-Based SegmentationWith Local Decision Fusion-Application to Cardiac and Aortic Segmentation in CT Scans. IEEE Trans. Med. Imag. 28(7), 1000–1010 (2009)
Rikxoort, E.M., Išgum, I., Arzhaeva, Y., Staring, M., Klein, S., Viergever, M., Pluim, J.P.W., van Ginneken, B.: Adaptive local multi-atlas segmentation: Application to the heart and the caudate nucleus. Medical Image Analysis (2010)
Zhuang, X., Rhode, K.S., Razavi, R.S., Hawkes, D.J., Ourselin, S.: A registration-based propagation framework for automatic whole heart segmentation of cardiac MRI. IEEE Trans. Med. Imag. 29(9), 1612–1625 (2010)
Kirişli, H.A., Schaap, M., Klein, S., Papadopoulou, S.L., Bonardi, M., Chen, C.H., Weustink, A.C., Mollet, N.R.A., Vonken, E.P.A., van der Geest, R.J., van Walsum, T., Niessen, W.J.: Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study. Medical Physics 37(12), 6279–6292 (2010)
Warfield, S.K., Zou, K.H., Wells, W.M.: Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image Segmentation. IEEE Trans. Med. Imag. 23(70), 903–921 (2004)
Ourselin, S., Roche, S., Subsol, G., Pennec, X., Ayache, N.: Reconstructing a 3D structure from serial histological sections. Image and Vis. Comp. 19(1-2), 25–31 (2001)
Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid registration using freeform deformations: Application to breast MR images. IEEE Trans. Med. Imag. 18(8), 712–721 (1999)
Modat, M., Ridgway, G.R., Taylor, Z.A., Lehmann, M., Barnes, J., Fox, N.C., Hawkes, D.J., Ourselin, S.: Fast free-form deformation using graphics processing units. Comput. Methods Programs Biomed. 98(3), 278–284 (2010)
Cardoso, M.J., Modat, M., Keihaninejad, S., Cash, D., Ourselin, S.: Multi-STEPS: multi-label similarity and truth estimation for propagated segmentations. In: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), pp. 153–158 (2012)
Uribe, S., Tangchaoren, T., Parish, I., Wolf, R., Razavi, R., Greil, G., Schaeffter, T.: Volumetric cardiac quantification by using 3-D dual phase whole-heart MR imaging. Radiology 248, 606–614 (2008)
Leung, K.K., Barnes, J., Ridgway, G.R., Bartlett, J.W., Clarkson, M.J., Macdonald, K., Schu, N., Fox, N.C., Ourselin, S.: ADNI: Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer’s disease. NeuroImage 51(4), 1345–1359 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zuluaga, M.A., Cardoso, M.J., Modat, M., Ourselin, S. (2013). Multi-atlas Propagation Whole Heart Segmentation from MRI and CTA Using a Local Normalised Correlation Coefficient Criterion. In: Ourselin, S., Rueckert, D., Smith, N. (eds) Functional Imaging and Modeling of the Heart. FIMH 2013. Lecture Notes in Computer Science, vol 7945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38899-6_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-38899-6_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38898-9
Online ISBN: 978-3-642-38899-6
eBook Packages: Computer ScienceComputer Science (R0)