Grade-spatial procedure in grade decomposition of medical images

• Autorzy: Grzegorek M.
• Języki publikacji: EN

Abstrakty

EN

The paper describes decomposition of gray medical images. Pixels of the image are assigned with the variable values derived from a neighbourhood of the pixel. Then Grade Correspondence Cluster Analysis is used to order set of pixels according to their grade differentiation and to divide pixels into subsets. Subsets are visualized in separate subimages and regions are extracted on principle of spatial neighbourhood in subimage. Influence of a number of subimages is discussed. Then a new grade-spatial procedure is proposed which combines features of grade similarity and spatial neighbourhoods.

Słowa kluczowe

EN

grade correspondence analysis; image grade decomposition; region; hidden structure

PL

gradacyjna analiza korespondencji; region; ukryte struktury

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2011
• Tom: Vol. 17
• Strony: 203--209
• Opis fizyczny: Bibliogr. 9 poz., rys.

Twórcy

autor

Grzegorek M.

• Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237 Warsaw, Poland

Bibliografia

• [1] ARBELÁEZ P., MAIRE M., FOWLKES C., MALIK J., Contour Detection and Hierarchical Image Segmentation, IEEE Trans. PAMI, Vol. 33, No. 5, 2011, pp. 898-916.
• [2] COMANICIU D., MEER P., Mean shift: A robust approach toward feature space analysis, IEEE Trans. PAMI, Vol. 24, No. 5, 2002, pp. 603-619.
• [3] GradeStat web site http://gradestat.ipipan.waw.pl/.
• [4] GRZEGOREK M., Variables Applied in a NMR Image Decomposition with the Aid of GCCA, Journal of Medical Informatics & Technologies, Vol. 12, 2008, pp. 183-187.
• [5] GRZEGOREK M., Grade Differentiation Measure of Images, in: KURZYŃSKI M, WOŻNIAK M. (eds.), Computer Recognition Systems 3, Advances in Soft Computing, Springer, Berlin Heidelberg, 2009, pp. 63-70.
• [6] GRZEGOREK M., Variable Complexity Reduction in Image Grade Decomposition, in: BURDUK R., KURZYŃSKI M., WOŹNIAK M., ŻOŁNIEREK A. (eds.), Computer Recognition Systems 4, Advances in Soft Computing, Springer, Berlin Heidelberg, 2011, pp. 239-247.
• [7] KOWALCZYK T., PLESZCZYŃSKA E., RULAND F., Grade Models and Methods for Data Analysis, With Applications for the Analysis of Data Populations, Studies in Fuzziness and Soft Computing, Springer, Berlin Heidelberg, New York, 2004.
• [8] SHI J., MALIK J., Normalized cuts and image segmentation, IEEE Trans. PAMI, Vol. 8, No. 22, 2000, pp. 731-737.
• [9] SZELISKI R., Computer Vision Algorithms and Applications, Springer, London Dordrecht Heidelberg, New York, 2011.