Abstract
This work aims at developing an automatic method for the analysis of TLC images for measuring a set of features that can be used for the characterization of the distinctive patterns that result from the separation of oligosaccharides contained in human urine. This paper describes the methods developed for the automatic detection of the lanes contained in TLC images, and for the automatic separation of bands for each detected lane. The extraction of quantitative information related with each band was accomplished with two methods: the EM expectation-maximization and nonlinear least squares trust-region algorithms. The results of these methods, as well as additional quantitative information related with each band, are also presented.
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.
Similar content being viewed by others
References
Sewell, A.: Urinary Oligosaccharides. In: Techniques in Diagnostic Human Biochemical Genetics, pp. 219–231. Willey-Liss, Inc (1991)
Thomas, G.: Disorders of Glycoprotein Degradation. α-Mannosidosis, β-Mannosidosis, Fucosidosis and Sialidosis. Disorders of Glycoprotein Degradation, ch. 140
Starr, C., Masada, R., Hague, C., Klock, J.: Fluorophore-assisted Carbohydrate Electrophoresis in the Separation, Analysis, and Sequencing of Carbohydrates. Journal of Chromatography A 720, 295–321 (1996)
Klein, A., Lebreton, A., Lemoine, J., Périni, J., Roussel, P., Michalski, J.: Identification of Urinary Oligosaccharides by Matrix-assisted Laser Desorption Ionization Time-of-flight Mass Spectrometry. Clinical Chemistry 44 (12), 2422–2428 (1998)
Dempster, A., Laird, N., Rubin, D.: Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, B 39(1), 1–38 (1977)
Schwedt, G.: The Essential Guide to Analytical Chemistry. John Wiley & Sons, Chichester
Dennis, J.: Nonlinear Least-squares, State of the Art in Numerical Analysis. D. Jacobs Academic Press, London
Byrd, R., Schnabel, R., Shultz, G.: Approximate Solution of the Trust Region Problem by Minimization over Two-Dimensional Subspaces. Mathematical Programming 40, 247–263 (1988)
Branch, M., Coleman, T., Li, Y.: A Subspace, Interior, and Conjugate Gradient Method for Large-Scale Bound-Constrained Minimization Problems. SIAM SISC 21(1), 1–23 (1999)
Nabney, I.: Netlab Algorithms for Pattern Recognition. In: Advances in Pattern Recognition, Springer, Heidelberg (2003)
Marques, J.: Reconhecimento de Padrões. Métodos Estatísticos e Neuronais. IST-Press, Orlando
Machado, A., Campos, M., Siqueira, A., Carvalho, O.: An Iterative Algorithm for Segmenting Lanes in Gel Electrophoresis Images (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sousa, A.V., Aguiar, R., Mendonça, A.M., Campilho, A. (2004). Automatic Lane and Band Detection in Images of Thin Layer Chromatography. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_20
Download citation
DOI: https://doi.org/10.1007/978-3-540-30126-4_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23240-7
Online ISBN: 978-3-540-30126-4
eBook Packages: Springer Book Archive