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This article is cited in 3 scientific papers (total in 3 papers)
IMAGE PROCESSING, PATTERN RECOGNITION
A method for digital renal scintigram analysis based on brightness and geometric features
A. V. Gaidelab, A. G. Khramova, A. V. Kapishnikovc, A. V. Kolsanovc, Yu. S. Pyshkinac a Samara National Research University, Samara, Russia
b Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia
c Samara State Medical University, Samara, Russia
Abstract:
We proposed a method of automated scintigram image processing enabling an objective evaluation of the renal parenchyma condition to be made based on scintigram brightness and geometric characteristics with threshold processing. We studied the method using a set of real radionuclide images of a renal transplant. The results of clinical studies confirm the effectiveness of the developed method. We obtained objective numerical values associated with thresholding the image from 40% to 80%, based on which one can form an independent assessment of the presence or absence of focal lesions in the renal parenchyma.
Keywords:
image processing, pattern recognition, scintigraphy, kidney disease, transplantation.
Received: 24.10.2016 Accepted: 06.12.2016
Citation:
A. V. Gaidel, A. G. Khramov, A. V. Kapishnikov, A. V. Kolsanov, Yu. S. Pyshkina, “A method for digital renal scintigram analysis based on brightness and geometric features”, Computer Optics, 41:1 (2017), 103–109
Linking options:
https://www.mathnet.ru/eng/co363 https://www.mathnet.ru/eng/co/v41/i1/p103
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