Abstract
We present an active surface model designed for the segmentation of Drosophila Schneider cell nuclei and nucleoli from wide-field microscopic data. The imaging technique as well as the biological application impose some major challenges to the segmentation. On the one hand, we have to deal with strong blurring of the 3D data, especially in z-direction. On the other hand, concerning the biological application, we have to deal with non-closed object boundaries and touching objects. To cope with these problems, we have designed a fully 3D active surface model. Our model prefers roundish object shapes and especially imposes roughly spherical surfaces where there is little gradient information. We have adapted an external force field for this model, which is based on gradient vector flow (\(\text{\it{GVF}}\)) and has a much larger capture range than standard \(\text{\it{GVF}}\) force fields.
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References
Ballard, D.H.: Generalizing the hough transform to detect arbitrary shapes. Pattern Recognition 13(2), 111–122 (1981)
Ronneberger, O., Wang, Q., Burkhardt, H.: Fast and robust segmentation of spherical particles in volumetric data sets from brightfield microscopy. In: Proc. of the ISBI, pp. 372–375 (2008)
Schulz, J., Schmidt, T., Ronneberger, O., Burkhardt, H., Pasternak, T., Dovzhenko, A., Palme, K.: Fast scalar and vectorial grayscale based invariant features for 3d cell nuclei localization and classification. In: Proc. of the DAGM, Berlin (2006)
Geusebroek, J.-M., Ter Haar Romeny, B., Koenderink, J., van den Boomgaard, R., van Osta, P.: Color differential structure. In: Front-End Vision and Multi-Scale Image Analysis, Computational Imaging and Vision, vol. 27. Springer, Netherlands (2003)
Xu, C., Prince, J.L.: Snakes, shapes, and gradient vector flow. IEEE Trans. Imag. Proc. 7(3), 321–345 (1998)
Montagnat, J., Delingette, H., Ayache, N.: A review of deformable surfaces: topology, geometry and deformation. Image and Vision Computing 19/14, 1023–1040 (2001)
He, L., Peng, Z., Everding, B., Wang, X., Han, C.Y., Weiss, K.L., Wee, W.G.: A comparative study of deformable contour methods on medical image segmentation. Image and Vision Computing 26/2, 141–163 (2008)
Yushkevich, P.A., Piven, J., Hazlett, C., Smith, H., Smith, G., Ho, R., Ho, S., Gee, J.C., Gerig, G.: User-Guided 3D Active Contour Segmentation of Anatomical Structures: Significantly Improved Efficiency and Reliability. Neuroimage 31/3, 1116–1128 (2006)
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Keuper, M., Padeken, J., Heun, P., Burkhardt, H., Ronneberger, O. (2009). A 3D Active Surface Model for the Accurate Segmentation of Drosophila Schneider Cell Nuclei and Nucleoli. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10331-5_80
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DOI: https://doi.org/10.1007/978-3-642-10331-5_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10330-8
Online ISBN: 978-3-642-10331-5
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