Abstract
We present a novel method for deriving a structural model of a plant root system from 3D Magnetic Resonance Imaging (MRI) data of soil grown plants and use it for plant root system analysis. The structural model allows calculation of physiologically relevant parameters. Roughly speaking, MRI images show local water content of the investigated sample. The small, local amounts of water in roots require a relatively high resolution, which results in low SNR images. However, the spatial resolution of the MRI images remains coarse relative to the diameter of typical fine roots, causing many gaps in the visible root system. To reconstruct the root structure, we propose a three step approach: 1) detect tubular structures, 2) connect all pixels to the base of the root using Dijkstras algorithm, and 3) prune the tree using two signal strength related thresholds. Dijkstras algorithm determines the shortest path of each voxel to the base of the plant root, weighing the Euclidean distance measure by a multi-scale vesselness measure. As a result, paths running within good root candidates are preferred over paths in bare soil. We test this method using both virtually generated MRI images of Maize and real MRI images of Barley roots. In experiments on synthetic data, we show limitations of our algorithm with regard to resolution and noise levels. In addition we show how to use our reconstruction for root phenotyping on real MRI data of barley roots and snow pea in soil. Extending our conference publication [1], we show how to use the structural model to remove unwanted structures, like underground weeds.
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References
Schulz, H., Postma, J.A., van Dusschoten, D., Scharr, H., Behnke, S.: 3D Reconstruction of Plant Roots from MRI Images. In: Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP), Rome, Italy (2012)
Waisel, Y., Eshel, A., Kafkafi, U. (eds.): Plant Roots: The Hidden Half. Marcel Dekker, Inc. (2002)
Nakanishi, T., Okuni, Y., Furukawa, J., Tanoi, K., Yokota, H., Ikeue, N., Matsubayashi, M., Uchida, H., Tsiji, A.: Water movement in a plant sample by neutron beam analysis as well as positron emission tracer imaging system. Journal of Radioanalytical and Nuclear Chemistry 255, 149–153 (2003)
Pierret, A., Doussan, C., Garrigues, E., Kirby, J.M.: Observing plant roots in their environment: current imaging options and specific contribution of two-dimensional approaches. Agronomy for Sustainable Development 23, 471–479 (2003)
Ferreira, S., Senning, M., Sonnewald, S., Keßling, P.M., Goldstein, R., Sonnewald, U.: Comparative transcriptome analysis coupled to x-ray ct reveals sucrose supply and growth velocity as major determinants of potato tuber starch biosynthesis. BMC Genomics. Online Journal 11 (2010)
Brown, J.M., Kramer, P.J., Cofer, G.P., Johnson, G.A.: Use of nuclear-magnetic resonance microscopy for noninvasive observations of root-soil water relations. Theoretical and Applied Climatology, 229–236 (1990)
Southon, T.E., Jones, R.A.: NMR imaging of roots – methods for reducing the soil signal and for obtaining a 3-dimensional description of the roots. Physiologia Plantarum, 322–328 (1992)
Jahnke, S., Menzel, M.I., van Dusschoten, D., Roeb, G.W., Bühler, J., Minwuyelet, S., Blümler, P., Temperton, V.M., Hombach, T., Streun, M., Beer, S., Khodaverdi, M., Ziemons, K., Coenen, H.H., Schurr, U.: Combined MRI-PET dissects dynamic changes in plant structures and functions. Plant Journal, 634–644 (2009)
Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale Vessel Enhancement Filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)
Lo, P., van Ginneken, B., de Bruijne, M.: Vessel tree extraction using locally optimal paths. In: Biomedical Imaging: From Nano to Macro, pp. 680–683 (2010)
Dowdy, R., Smucker, A., Dolan, M., Ferguson, J.: Automated image analyses for separating plant roots from soil debris elutrated from soil cores. Plant and Soil 200, 91–94 (1998)
Mühlich, M., Truhn, D., Nagel, K., Walter, A., Scharr, H., Aach, T.: Measuring Plant Root Growth. In: Rigoll, G. (ed.) DAGM 2008. LNCS, vol. 5096, pp. 497–506. Springer, Heidelberg (2008)
Armengaud, P., Zambaux, K., Hills, A., Sulpice, R., Pattison, R.J., Blatt, M.R., Amtmann, A.: Ez-rhizo: integrated software for the fast and accurate measurement of root system architecture. Plant Journal 57, 945–956 (2009)
Nagel, K.A., Schurr, U., Walter, A.: Dynamics of root growth stimulation in nicotiana tabacum in increasing light intensity. Plant Cell and Environment 29, 1936–1945 (2006)
Haber-Pohlmeier, S., van Dusschoten, D., Stapf, S.: Waterflow visualized by tracer transport in root-soil-systems using MRI. In: Geophysical Research Abstracts, vol. 11 (2009)
Tracy, S., Roberts, J., Black, C., McNeill, A., Davidson, R., Mooney, S.: The X-factor: visualizing undisturbed root architecture in soils using X-ray computed tomography. Journal of Experimental Botany 61, 311–313 (2010)
Haacke, E., Brown, R., Thompson, M., Venkatesan, R.: Magnetic Resonance Imaging, Physical Principles and Sequence Design. John Wiley & Sons (1999)
Postma, J.A., Lynch, J.P.: Root cortical aerenchyma enhances the acquisition and utilization of nitrogen, phosphorus, and potassium in zea mays l. Plant Physiology 156, 1190–1201 (2011)
Postma, J.A., Lynch, J.P.: Theoretical evidence for the functional benefit of root cortical aerenchyma in soils with low phosphorus availability. Annals of Botany 107, 829–841 (2011)
Lindeberg, T.: Edge detection and ridge detection with automatic scale selection. In: CVPR, pp. 465–470 (1996)
Krissian, K., Malandain, G., Ayache, N., Vaillant, R., Trousset, Y.: Model based multiscale detection of 3d vessels. In: Proceedings of the Workshop on Biomedical Image Analysis, pp. 202–210. IEEE (1998)
Dijkstra, E.: A note on two problems in connexion with graphs. Numerische Mathematik 1, 269–271 (1959)
van Rijsbergen, C.: Information Retrieval, 2nd edn. Butterworth, London (1979)
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Schulz, H., Postma, J.A., van Dusschoten, D., Scharr, H., Behnke, S. (2013). Plant Root System Analysis from MRI Images. In: Csurka, G., Kraus, M., Laramee, R.S., Richard, P., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Application. Communications in Computer and Information Science, vol 359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38241-3_28
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DOI: https://doi.org/10.1007/978-3-642-38241-3_28
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