Abstract
The article presents a decision based algorithm of an automatic identification of markers in microscope images—ISH (In Situ Hybridization). The ISH test allows a quick and inexpensive initial diagnosis of the breast cancer. The evaluation of a degree of the HER2 gene’s amplification and the selection of the appropriate treatment require locating and counting markers in cell nuclei. This article presents a new heterogeneous algorithm based on decision making. The main idea is to analyze a portion of an image and decide which algorithm should be used for processing the given fragment. The different parts of the image can be analyzed by different types of algorithms. Tests and results of the experiment are presented and discussed in this article. They confirm higher efficiency of markers recognition by the homogeneous system, using many different algorithms, rather than in the case of using the method based on a single algorithm.
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
References
Solorzano, C.O., Santos, A., Vallcorba, I., Garcia-Sagredo, J.-M., Pozo, F.: Automated fish spot counting in interphase nuclei: statistical validation and data correction. Cytometry 31(2), 93–99 (1998)
Pratt, W.K.: Digital image processing. Wiley, New York (1991)
Lerner, B., Clocksin, W.F., Dhanjal, S., Hulten, M.A., Bishop, C.M.: Feature representation and signal classification in fluorescence in-situ hybridization image analysis. IEEE Trans. Syst. Man Cybern. 31, 655–665 (2001)
Clocksin, W.F., Lerner, B.: Automatic analysis of fluorescence in situ hybridization images. In: Proceedings of the 11th British Machine Vision Conference, pp. 666–674, Bristol, England, Sept 2000
Kasampalidis, J.N., Pitas, I., Karayannopolou, G.: FISH image analysis using a modified radial basis function network. Signals Circ. Syst. ISSCS 2, 1–4 (2007)
Les, T., Markiewicz, T., Osowski, S., Cichowicz, M., Kozlowski, W.: Automatic evaluation system of fish images in breast cancer. In: Image and Signal Processing Lecture Notes in Computer Science, vol. 8509, pp. 332–339 (2014)
Les, T., Markiewicz, T., Osowski, T., Jesiotr, M., Kozlowski, W.: Localization of spots in FISH images of breast cancer using 3-D shape analysis. J. Microsc. 262(3) (2016) http://dx.doi.org/10.1111/jmi.12360
Les, T., Markiewicz, T., Osowski, S., Kozlowski, W., Jesiotr, M.: Fusion of FISH image analysis methods of HER2 status determination in breast cancer. Expert Syst. Appl. (2016). doi:10.1016/j.eswa.2016.05.020
Acknowledgment
This study was supported by the National Centre for Research and Development, Poland (grant PBS2/A9/21/2013).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Les, T., Markiewicz, T., Jesiotr, M., Kozlowski, W., Brzoskowska, U. (2017). Decision Based Algorithm for Gene Markers Detection in the ISH Images. In: Jabłoński, R., Szewczyk, R. (eds) Recent Global Research and Education: Technological Challenges. Advances in Intelligent Systems and Computing, vol 519. Springer, Cham. https://doi.org/10.1007/978-3-319-46490-9_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-46490-9_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46489-3
Online ISBN: 978-3-319-46490-9
eBook Packages: EngineeringEngineering (R0)