Gaussian pyramid reduction method for the extraction of pathological structures of the aorta

• Autorzy: Sobotnicka E. , Sobotnicki A. , Jeżewski J.
• Języki publikacji: EN

Abstrakty

EN

An analysis of the biomedical image in one scale may result in the loss of information contained in the image during an analysis in a different scale. This issue can be solved by an analysis performed simultaneously in all scales, which can be done through the application of the pyramid reduction method. The pyramid makes it possible to obtain images at various levels of detail, including significant information. The paper discusses the method of processing biomedical images of the aorta with the use of the pyramid reduction method, as well as the way in which the results can be used in the segmentation process. The Gaussian pyramid reduction method was used for pyramid representation, whereas the segmentation process was performed with the split and merge method.

Słowa kluczowe

EN

pyramid reduction; image analysis; split method; merge method; aorta structure visualization

PL

analiza obrazu; metoda podziału; metoda scalania; wizualizacja struktury aorty

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2017
• Tom: Vol. 26
• Strony: 37--44
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Sobotnicka E.

• Institute of Medical Technology and Equipment, 118 Roosevelt St., 41-800 Zabrze, Poland

autor

Sobotnicki A.

• Institute of Medical Technology and Equipment, 118 Roosevelt St., 41-800 Zabrze, Poland

autor

Jeżewski J.

• Institute of Medical Technology and Equipment, 118 Roosevelt St., 41-800 Zabrze, Poland

Bibliografia

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• [8] NOAH LEE, HUSEYIN TEK A. F. L. True-false lumen segmentation of aortic dissection using multi-scale wavelet analysis and generative-discriminative model matching. Proc.SPIE, 2008, Vol. 6915. pp. 6915-6915-11.
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• [12] SOBOTNICKA E., SOBOTNICKI A., HOROBA K., PORWIK P. The application of the region growing method to the determination of arterial changes. Computational Collective Intelligence: 8th International Conference, ICCCI 2016, Halkidiki, Greece, September 28-30, 2016. Proceedings, Part II, 2016. Springer International Publishing, Cham, pp. 462–471.
• [13] SOBOTNICKA E., WRÓBEL J., SOBOTNICKI A. Detection of aorta anatomical structures characterized by various levels of pixel intensity. 2016 MIXDES - 23rd International Conference Mixed Design of Integrated Circuits and Systems, June 2016. pp. 498–503.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).