Abstract
This paper considers the optimization of a set of brightness gradations for pixel images of the tissue morphology of patients with oncological pathology. The influence of a set of pixel brightness gradations on the functional performance of training a system for the recognition of images of oncological diseases is analyzed. It is established that a change in the collection of pixel brightnesses in the receptive field increases the value of the criterion of functional efficiency and, as a result, the reliability of recognition.
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S. V. Ablameyko and A. M. Nedzved, Processing of Optical Images of Cellular Structures in Medicine [in Russian], State United Institute of Informatics Problems of NAS of Belarus, Minsk (2005).
A. Belotserkovsky, A. Nedzved, S. Ablameyko, I. Gurevich, and O. Salvetti, “Automation of preliminary histological diagnostic of oncological diseases,” in: Proc. Intern. Conf. on Advanced Information and Telemedicine Technologies for Health (November 8–10, 2005), 1, Minsk, Belarus, United Institute of Informatics Problems of the National Academy of Sciences of Belarus, Minsk (2005), pp. 70–74.
K. N. Malyshevska, “Segmentation of irregular regions in medical images with the help of Kohonen cards,” Visnyk Cherkas. Derzh. Technolog. Univ-ta, No. 4, 32–35 (2010).
A. S. Krasnopoyasovsky, Information Synthesis of Intelligent Control Systems: An Approach Based on the Method of Functional-Statistical Tests [in Ukrainian], Vyd-vo SumDU, Sumy (2004).
A. S. Dovbysh, Foundations of Intelligent Systems Design [in Ukrainian], Vyd-vo SumDU, Sumy (2009).
A. S. Dovbysh, S. S. Martynenko, A. S. Kovalenko, and N. N. Budnyk, “Information-extreme algorithm for recognizing current distribution maps in magnetocardiography,” J. Automat. and Inform. Sci., 43, No. 2, 63–70 (2011).
I. V. Shelekhov and M. S. Rudenko, “Information-extreme algorithm for the optimization of threshold brightness parameters of morphological images in diagnosing oncopathologies,” Radioelectronic and Computer Systems, No 3(55) 94–100 (2012).
A. S. Dovbysh, A. M. Romanyuk, and M. S. Rudenko, “Frame identification in problems of recognition of images of medical and biological objects,” Bionics of Intelligence, No. 1 (78), 53–58 (2012).
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Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 178–184, January–February 2014.
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Dovbysh, A.S., Rudenko, M.S. Information-Extreme Learning Algorithm for a System of Recognition of Morphological Images in Diagnosing Oncological Pathologies. Cybern Syst Anal 50, 157–162 (2014). https://doi.org/10.1007/s10559-014-9603-y
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DOI: https://doi.org/10.1007/s10559-014-9603-y