Previous |  Up |  Next

Article

Title: 4D Embryogenesis image analysis using PDE methods of image processing (English)
Author: Bourgine, Paul
Author: Čunderlík, Róbert
Author: Drblíková-Stašová, Olga
Author: Mikula, Karol
Author: Remešíková, Mariana
Author: Peyriéras, Nadine
Author: Rizzi, Barbara
Author: Sarti, Alessandro
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 46
Issue: 2
Year: 2010
Pages: 226-259
Summary lang: English
.
Category: math
.
Summary: In this paper, we introduce a set of methods for processing and analyzing long time series of 3D images representing embryo evolution. The images are obtained by in vivo scanning using a confocal microscope where one of the channels represents the cell nuclei and the other one the cell membranes. Our image processing chain consists of three steps: image filtering, object counting (center detection) and segmentation. The corresponding methods are based on numerical solution of nonlinear PDEs, namely the geodesic mean curvature flow model, flux-based level set center detection and generalized subjective surface equation. All three models have a similar character and therefore can be solved using a common approach. We explain in details our semi-implicit time discretization and finite volume space discretization. This part is concluded by a short description of parallelization of the algorithms. In the part devoted to experiments, we provide the experimental order of convergence of the numerical scheme, the validation of the methods and numerous experiments with the data representing an early developmental stage of a zebrafish embryo. (English)
Keyword: image processing
Keyword: embryogenesis
Keyword: image analysis
Keyword: finite volume method
Keyword: image filtering
Keyword: object counting
Keyword: segmentation
Keyword: partial differential equation
MSC: 35A99
MSC: 35L60
MSC: 65D18
MSC: 65M08
MSC: 68U10
MSC: 74S10
MSC: 92C55
MSC: 94A08
idZBL: Zbl 1198.94020
idMR: MR2663599
.
Date available: 2010-09-13T16:39:13Z
Last updated: 2013-07-30
Stable URL: http://hdl.handle.net/10338.dmlcz/140742
.
Reference: [1] Aoyama, Y., Nakano, J.: RS/6000 SP: Practical MPI Programming.IBM 1999.
Reference: [2] Bourgine, P., Frolkovič, P., Mikula, K., Peyriéras, N., Remešíková, M.: Extraction of the intercellular skeleton from 2D microscope images of early embryogenesis.(Lecture Notes in Comp. Sci., 5567.) (Proc. 2nd Internat. Conference on Scale Space and Variational Methods in Computer Vision, Voss 2009), Springer, Berlin pp. 38–49.
Reference: [3] Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours.Internat. J. Comput. Vision 22 (1997), 61–79. Zbl 0894.68131, 10.1023/A:1007979827043
Reference: [4] Chen, Y., Vemuri, B. C., Wang, L.: Image denoising and segmentation via nonlinear diffusion.Comp. Math. Appl. 39 (2000), 131–149. Zbl 0951.68556, MR 1742478, 10.1016/S0898-1221(00)00050-X
Reference: [5] Corsaro, S., Mikula, K. , Sarti, A., Sgallari, F.: Semi-implicit co-volume method in 3D image segmentation.SIAM J. Sci. Comput. 28 (2006), 6, 2248–2265. MR 2272260, 10.1137/060651203
Reference: [6] Frolkovič, P., Mikula, K.: Flux-based level set method: A finite volume method for evolving interfaces.Appl. Numer. Math. 57 (2007), 4, 436–454. MR 2310759, 10.1016/j.apnum.2006.06.002
Reference: [7] Frolkovič, P., Mikula, K., Peyrieras, N., Sarti, A.: A counting number of cells and cell segmentation using advection-diffusion equations.Kybernetika 43 (2007), 6, 817–829. MR 2388396
Reference: [8] Huttenlocher, D. P., Klanderman, G. A., Rucklidge, W. J.: Comparing images using the Hausdorff distance.IEEE Trans. Pattern Analysis and Machine Intelligence 15 (1993), 9, xxx–xxx.
Reference: [9] Kichenassamy, S., Kumar, A., Olver, P., Tannenbaum, A., Yezzi, A.: Conformal curvature flows: from phase transitions to active vision.Arch. Rational Mech. Anal. 134 (1996), 275–301. Zbl 0937.53029, MR 1412430, 10.1007/BF00379537
Reference: [10] Krivá, Z., Mikula, K., Peyriéras, N., Rizzi, B., Sarti, A.: Zebrafish early embryogenesis 3D image filtering by nonlinear partial differential equations.Medical Image Analysis. Submitted for publication.
Reference: [11] Mikula, K., Peyriéras, N., Remešíková, M., Sarti, A.: 3D embryogenesis image segmentation by the generalized subjective surface method using the finite volume technique.In: Proc. FVCA5 – 5th International Symposium on Finite Volumes for Complex Applications, Hermes Publ. Paris 2008.
Reference: [12] Mikula, K., Remešíková, M.: Finite volume schemes for the generalized subjective surface equation in image segmentation.Kybernetika 45 (2009), 4, xxx–xxx. MR 2588630
Reference: [13] Mikula, K., Sarti, A.: Parallel co-volume subjective surface method for 3D medical image segmentation.Parametric and Geometric Deformable Models: An application in Biomaterials and Medical Imagery, Vol. II, Springer Publishers, 2007, pp. 123–160.
Reference: [14] Sarti, A., Malladi, R., Sethian, J. A.: Subjective surfaces: A method for completing missing boundaries.In: Proc. National Academy of Sciences of the United States of America 12 (2000), 97, 6258–6263. Zbl 0966.68214, MR 1760935
Reference: [15] Tassy, O., Daian, F., Hudson, C., Bertrandt, V., Lemaire, P.: A quantitative approach to the study of the cell shapes and interactions during early chordate embryogenesis.Currrent Biology 16 (2006), 345–358. 10.1016/j.cub.2005.12.044
Reference: [16] Yushkevich, P. A., Piven, J., Hazlett, H. Cody, Smith, R. Gimpel, Ho, S., Gee, J. C., Gerig, G.: User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability.Neuroimage 31 (2006), 3, 1116–28. 10.1016/j.neuroimage.2006.01.015
Reference: [17] Zanella, C., Campana, M., Rizzi, B., Melani, C., Sanguinetti, G., Bourgine, P., Mikula, K., Peyriéras, N., Sarti, A.: Cells segmentation from 3-D confocal images Of early zebrafish embryogenesis.IEEE Trans. Image Process. 19 (2010), 3, 770–781. MR 2756569, 10.1109/TIP.2009.2033629
Reference: [18] Zhang, J. W., Han, G. Q., Wo, Y.: Image registration based on generalized and mean Hausdorff distances.In: Proc. Fourth International Conference on Machine Learning and Cybernetics, Guangzhou 2005.
.

Files

Files Size Format View
Kybernetika_46-2010-2_3.pdf 4.423Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo