Abstract
The need for high-throughput quantification of cell growth and cell division in a multilayer, multicellular tissue necessitates the development of an automated image analysis pipeline that is capable of processing high volumes of live imaging microscopy data. In this work, we present such an image processing and analysis pipeline that combines cell image registration, segmentation, tracking, and cell resolution 3D reconstruction for confocal microscopy-based time-lapse volumetric image stacks. The first component of the pipeline is an automated landmark-based registration method that uses a local graph-based approach to select a number of landmark points from the images and establishes correspondence between them. Once the registration is acquired, the cell segmentation and tracking problem is jointly solved using an adaptive segmentation and tracking module of the pipeline, where the tracking output acts as an indicator of the quality of segmentation and in turn the segmentation can be improved to obtain better tracking results. In the last module of our pipeline, an adaptive geometric tessellation-based 3D reconstruction algorithm is described, where complete 3D structures of individual cells in the tissue are estimated from sparse sets of 2D cell slices, as obtained from the previous components of the pipeline. Through experiments on Arabidopsis shoot apical meristems, we show that each component in the proposed pipeline provides highly accurate results and is robust to ‘Z-sparsity’ in imaging and low SNR at parts of the collected image stacks.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Chakraborty A, Perales M, Reddy GV, Roy-Chowdhury AK (2013) Adaptive geometric tessellation for 3D reconstruction of anisotropically developing cells in multilayer tissues from sparse volumetric microscopy images. PLoS ONE
Liu M, Yadav RK, Roy-Chowdhury A, Reddy GV (2010) Automated tracking of stem cell lineages of Arabidopsis shoot apex using local graph matching. Plant J
Vincent L, Soille P (1991) Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans Pattern Anal Mach Intell
Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P (1997) Multimodality image registration by maximization of mutual information. IEEE Trans Med Imaging
Viola P, Wells WM (1997) Alignment by maximization of mutual information. Int J Comput Vis
Fernandez R, Das R, Mirabet V, Moscardi E, Traas J, Verdeil J, Malandain G, Godin C (2010) Imaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolution. Nat Methods
Besl P, McKay N (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal Mach Intell
Sharp GC, Lee SW, Wehe DK (2002) Invariant features and the registration of rigid bodies. IEEE Trans Pattern Anal Mach Intell
Mkrtchyan K, Chakraborty A, Roy-Chowdhury A (2013) Automated registration of live imaging stacks of Arabidopsis. In: International symposium on biomedical imaging
Reddy GV, Meyerowitz EM (2005) Stem-cell homeostasis and growth dynamics can be uncoupled in the Arabidopsis shoot apex. Science
Chan T, Vese L (2001) Active contours without edges. IEEE Trans Image Process
Li K, Kanade T (2007) Cell population tracking and lineage construction using multiple-model dynamics filters and spatiotemporal optimization. Microscop Image Anal Appl Biol
Cunha AL, Roeder AHK, Meyerowitz EM (2010) Segmenting the sepal and shoot apical meristem of Arabidopsis thaliana. Annu Int Conf IEEE Eng Med Biol Soc
Chui H (2000) A new algorithm for non-rigid point matching. IEEE Comput Soc Conf Comput Vis Pattern Recogn
Gor V, Elowitz M, Bacarian T, Mjolsness E (2005) Tracking cell signals in fluorescent images. In: IEEE workshop on computer vision methods for bioinformatics
Rangarajan A, Chui H, Bookstein FL (2005) The soft assign procrustes matching algorithm. Inf Process Med Imag
Liu M, Chakraborty A, Singh D, Gopi M, Yadav R, Reddy GV, Roy-Chowdhury A (2011) Adaptive cell segmentation and tracking for volumetric confocal microscopy images of a developing plant meristem. Mol Plant
Chakraborty A, Roy-Chowdhury A (2014) Context aware spatio-temporal cell tracking in densely packed multilayer tissues. Med Image Anal
Chakraborty A, Roy-Chowdhury A (2014) A conditional random field model for tracking in densely packed cell structures. IEEE Int Conf Image Process
Beucher S, Lantuejoul C (1979) Use of watersheds in contour detection. In: International workshop on image processing: realtime edge and motion detection/estimation
Najman L, Schmitt M (1994) Watershed of a continuous function. Signal Process
Marcuzzo M, Quelhas P, Campilho A, Mendonca AM, Campilho AC (2008) Automatic cell segmentation from confocal microscopy images of the Arabidopsis root. In: IEEE international symposium on biomedical imaging
Soille P (2003) Morphological image analysis: principles and applications, 2nd edn. Springer, New York
Nakahari T, Murakami M, Yoshida H, Miyamoto M, Sohma Y, Imai Y (1990) Decrease in rat submandibular acinar cell volume during ACh stimulation. Am J Physiol
Farinas J, Kneen M, Moore M, Verkman AS (1997) Plasma membrane water permeability of cultured cells and epithelia measured by light microscopy with spatial filtering. J General Physiol
Kawahara K, Onodera M, Fukuda Y (1994) A simple method for continuous measurement of cell height during a volume change in a single A6 cell. Jpn J Physiol
Kwiatkowska D, Routier-Kierzkowska A (2009) Morphogenesis at the inflorescence shoot apex of Anagallis arvensis: surface geometry and growth in comparison with the vegetative shoot. J Exp Botany
Tataw O, Liu M, Yadav R, Reddy V, Roy-Chowdhury A (2010) Pattern analysis of stem cell growth dynamics in the shoot apex of Arabidopsis. IEEE Int Conf Image Process
Zhu Q, Tekola P, Baak JP, Belikin JA (1994) Measurement by confocal laser scanning microscopy of the volume of epidermal nuclei in thick skin sections. Anal Quant Cytol Histol
Errington RJ, Fricker MD, Wood JL, Hall AC, White NS (1997) Four-dimensional imaging of living chondrocytes in cartilage using confocal microscopy: a pragmatic approach. Am J Physiol
Chakraborty A, Yadav RK, Reddy GV, Roy-Chowdhury A (2011) Cell resolution 3D reconstruction of developing multilayer tissues from sparsely sampled volumetric microscopy images. IEEE Int Conf Bioinform Biomed
Mjolsness E (2006) The growth and development of some recent plant models: a viewpoint. J Plant Growth Regul (Springer)
Gor V, Shapiro BE, Jönsson H, Heisler M, Reddy GV, Meyerowitz EM, Mjolsness E (2005) A software architecture for developmental modelling in plants: the computable plant project. Bioinf Genome Regul Struct
Boissonnat J, Wormser C, Yvinec M (2006) Curved Voronoi diagrams, effective computational geometry for curves and surfaces. Mathematics and visualization. Springer
Khachiyan LG (1996) Rounding of polytopes in the real number model of computation. Math Methods Oper Res
Kumar P, Yildirim EA (2005) Minimum-volume enclosing ellipsoids and core sets. J Opt Theory Appl
Acknowledgment
We gratefully acknowledge Prof. Venugopala Reddy from Plant Biology at the University of California, Riverside for providing us the datasets on which results are shown. This work was supported in part by the National Science Foundation Integrative Graduate Education and Research Traineeship (IGERT) in Video Bioinformatics (DGE-0903667). Katya Mkrtchyan is an IGERT Fellow.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Mkrtchyan, K., Chakraborty, A., Liu, M., Roy-Chowdhury, A. (2015). Automatic Image Analysis Pipeline for Studying Growth in Arabidopsis. In: Bhanu, B., Talbot, P. (eds) Video Bioinformatics. Computational Biology, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-23724-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-23724-4_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23723-7
Online ISBN: 978-3-319-23724-4
eBook Packages: Computer ScienceComputer Science (R0)